code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
snake_case_ : Tuple = logging.get_logger(__name__)
... | 212 |
'''simple docstring'''
# Copyright 2021 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/LIC... | 212 | 1 |
def UpperCAmelCase ( lowerCAmelCase__ ):
'''simple docstring'''
return str(lowerCAmelCase__ ) == str(lowerCAmelCase__ )[::-1]
def UpperCAmelCase ( lowerCAmelCase__ ):
'''simple docstring'''
return int(lowerCAmelCase__ ) + int(str(lowerCAmelCase__ )[::-1] )... | 205 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 205 | 1 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE=() ... | 102 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
'''simple docstring'''
__SCREAMING_SNAKE_CASE : Any = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
__SCREAMING_SNAKE_CASE : str = ['a', 'b', 'c', 'd', 'e']
def _snake_case ( lowercase , lowercase , lowercase ) -> Union[str... | 710 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : Optional[Any] = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARC... | 697 | 0 |
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
'The converted tokenizer will be ... | 562 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : str = {
'ksst... | 226 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : List[str] = logging.get_logger(__name__)
lowercase_ : List[Any] = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingfac... | 717 |
def A__( __lowerCAmelCase ):
assert column_title.isupper()
_snake_case : List[Any] = 0
_snake_case : List[str] = len(__lowerCAmelCase ) - 1
_snake_case : Dict = 0
while index >= 0:
_snake_case : List[str] = (ord(column_ti... | 652 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependen... | 665 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_n... | 665 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A ( UpperCAmelCas... | 654 | '''simple docstring'''
import heapq
import sys
import numpy as np
__lowerCAmelCase : Any = tuple[int, int]
class A :
def __init__( self : Optional[int] ) -> int:
__UpperCAmelCase = []
__UpperCAmelCase ... | 654 | 1 |
"""simple docstring"""
import numpy as np
def UpperCamelCase ( _A ) -> np.ndarray:
return 1 / (1 + np.exp(-vector ))
def UpperCamelCase ( _A ) -> np.ndarray:
return vector * sigmoid(_A )
if __name__ == "__main__":
import doctest
doctest.test... | 264 |
"""simple docstring"""
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def UpperCamelCase ( _A = "laptop" ) -> DataFrame:
lowercase : List[str] = F"""https://www.amazon.in/laptop/s?k={product}"""
low... | 264 | 1 |
'''simple docstring'''
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_... | 654 | '''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : Tuple ):
"""simple docstring"""
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
__UpperCAmelCase = len(UpperCamelCase__ )
__... | 654 | 1 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def lowerCamelCase__ ( _A ):
'''simple docstring'''
snake_case_ = os.path.join(args.tf_model_dir , "parame... | 376 |
import numpy as np
def lowerCamelCase__ ( _A ):
'''simple docstring'''
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 376 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Tuple = logging.get_logger(__name__)
_A : List[str] = {
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltCLIP/res... | 713 |
"""simple docstring"""
# flake8: noqa
# Lint as: python3
_A : Dict = [
"""VerificationMode""",
"""Version""",
"""disable_progress_bar""",
"""enable_progress_bar""",
"""is_progress_bar_enabled""",
"""experimental""",
]
from .info_utils import VerificationMode
from ... | 518 | 0 |
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
SCREA... | 112 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
SCREAMING_SNAKE_CASE__ : List[str] = Path(__file__).resolve().parents[3] / """src"""
sys.path.insert(1, str(git_repo_path))
import dataclas... | 112 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_chann... | 435 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase_ = {
'configuration_roberta_prelayernorm': [
'ROBERTA_PRELAYERNORM_PRETRAINE... | 435 | 1 |
SCREAMING_SNAKE_CASE__ : Dict = [
(1_0_0_0, """M"""),
(9_0_0, """CM"""),
(5_0_0, """D"""),
(4_0_0, """CD"""),
(1_0_0, """C"""),
(9_0, """XC"""),
(5_0, """L"""),
(4_0, """XL"""),
(1_0, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1... | 112 |
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ... | 112 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A = logging.get_logger(__name__)
A = {
'google/bit-50': 'https://huggingface.co/google/bit-50/resolve/... | 701 |
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_configuration_common import ConfigTest... | 46 | 0 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def A ( __UpperCamelCase , __UpperCamelCase=7 ) -> Optional[int]:
A__ = None
if token is not None:
A__ = {'Accept': 'application/vnd.github+json',... | 9 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
)
| 620 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase... | 716 |
"""simple docstring"""
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 ... | 598 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async... | 252 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=__lowerCamelCase )
class a ( __lowerCamelCase ):
# `task` is not a ClassVar since we want it to be part o... | 252 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def lowerCamelCase_ ( __lowerCAmelCase = 150_0000 ) -> int:
'''simple docstring'''
lowerCamelCase__ =defaultdict(__lowerCAmelCase )
lowerCamelCase__ =2
while... | 132 | """simple docstring"""
import heapq
import sys
import numpy as np
a =tuple[int, int]
class __UpperCAmelCase :
def __init__( self ):
lowerCamelCase__ =[]
lowerCamelCase__ =set()
def _a ( self ):
if not self.empty():
return... | 132 | 1 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.nn as nn
from ... | 307 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers.mod... | 307 | 1 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase ( lowercase_ : int , lowercase_ : int ) -> tuple[int, int]:
'''simple docstring'''
if b == 0:
return (1, 0)
((lowercase) , (lowercase)) =extended_euclid(lowercase_ , a ... | 706 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimen... | 145 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtracti... | 58 | import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
_UpperCAmelCase = {
"""n_samples""": 64,
"""horizon""": 32,
"""num_inference_steps""": 20,
"""n_guide_steps""": 2, # can set to 0 for faster sampling, does not use value network... | 558 | 0 |
from math import isqrt, loga
def __UpperCamelCase ( _lowerCAmelCase ) -> list[int]:
"""simple docstring"""
A : Tuple = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , _lowerCAmelCas... | 520 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils impo... | 520 | 1 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.modeling_fl... | 547 | from __future__ import annotations
from collections import Counter
from random import random
class _UpperCAmelCase :
'''simple docstring'''
def __init__( self : List[str]) -> Any:
"""simple docstring"""
_UpperCamelCase = {}
def __UpperCAmelCase ( ... | 547 | 1 |
'''simple docstring'''
from itertools import product
def _snake_case ( lowercase , lowercase ) -> list[int]:
__a : Optional[int] = sides_number
__a : Union[str, Any] = max_face_number * dice_number
__a : Optional[Any] ... | 697 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class SCREAMING_SNAKE_CASE__ ( __UpperCamelCase ):
def __init__( self , __UpperCamelCase , __UpperCamelCase ):
'''simple docst... | 697 | 1 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( _lowercase : Union[str, Any] , _lowercase : ... | 266 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase: List[Any] = logging.get_logger(__name__)
__UpperCamelCase: Dict = {
"""studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json""",
"""studio-ousi... | 266 | 1 |
'''simple docstring'''
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_model... | 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Optional[int] = logging.get_logger(__name__)
__A : List[Any] = {
'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
'studio-o... | 267 | 1 |
import math
from datetime import datetime, timedelta
def lowercase( UpperCamelCase_ ) -> str:
'''simple docstring'''
UpperCamelCase = year % 19
UpperCamelCase = year % 4
UpperCamelCase = year % 7
UpperCamelCase = math.floor(year / 100 )
UpperCamelCas... | 537 |
"""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 Pr... | 609 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_out... | 389 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
snake_case__ : Optional[int] = {
'''configuration_speecht5''': [
'''SPEECHT5_PRETRAINED_CONFIG_ARC... | 389 | 1 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from transf... | 193 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Any = {
"configuration_chinese_clip": [
"CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"ChineseCLIPConfig",
"ChineseCLIPOn... | 193 | 1 |
'''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 ( __lowercase):
"""simple docstring"""
def __init__( self , __A , ... | 58 | '''simple docstring'''
def UpperCamelCase__ ( a__ = 1_0_0_0 ):
'''simple docstring'''
_lowerCAmelCase =2**power
_lowerCAmelCase =0
while n:
_lowerCAmelCase , _lowerCAmelCase =r + n % 1_0, n // 1_0
return r
if __name_... | 58 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
log... | 48 | '''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __A :
a__ : int
a__ : TreeNode | None = None
a__ : TreeNode | None = None
SCREAMING_SNAKE_CASE_: Union[str, Any] =namedtu... | 78 | 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 ... | 472 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...test_conf... | 472 | 1 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __A (_SCREAMING_SNAKE_CASE ) ->Optional[int]:
"""simple docstring"""
return getitem, k
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE... | 93 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
"""microsoft/xprophetnet-large-wiki100-cased""": (
"""https://huggingface.co/microsof... | 437 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_utils import is_... | 701 |
from __future__ import annotations
from typing import Any
class _snake_case :
'''simple docstring'''
def __init__( self: Optional[int] ,lowerCamelCase_: int = 6 ) -> None:
UpperCAmelCase_ : Node | None = None
UpperCAmelCase_ ... | 322 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Tuple = logging.get_logger(__name__)
__magic_name__ : Optional[int] = {
'''BridgeTower/bridgetower-base''': '''ht... | 497 |
'''simple docstring'''
from typing import Any
def A__ ( A_ ) -> list[Any]:
if not input_list:
return []
_lowercase = [input_list.count(A_ ) for value in input_list]
_lowercase = max(A_ ) # Gets the maximum count in the input list.
# Gets values of modes
... | 497 | 1 |
"""simple docstring"""
from functools import lru_cache
def __magic_name__ ( __snake_case : int ) -> set:
lowercase : List[str] = 2
lowercase : Union[str, Any] = set()
while i * i <= n:
if n % i:
... | 715 |
"""simple docstring"""
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
_A : Any = """."""
if __name__ == "__main__":
_A : Any = os.path.join(REPO_PATH, """utils/documentati... | 518 | 0 |
"""simple docstring"""
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_m... | 661 |
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
cla... | 14 | 0 |
import math
def lowerCamelCase_ ( UpperCamelCase__ : list, UpperCamelCase__ : int = 0, UpperCamelCase__ : int = 0 ):
'''simple docstring'''
UpperCamelCase__ = end or len(UpperCamelCase__ )
for i in range(UpperCamelCase__, UpperCam... | 591 | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 591 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Tuple , __snake_case : int ) -> bool:
__A : Any = len(A__ )
__A : Dict = len(A__ )
__A : Dict = [[False for _ in range(m + 1 )] for _ in r... | 8 |
'''simple docstring'''
def __a ( A__ = 1000 ) -> int:
lowerCAmelCase = 3
lowerCAmelCase = 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__ == "__main__... | 649 | 0 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase ) -> bool:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
_lowerCamelCase : List[str] = F"""Input value of [number={number}] must be an integer"""
raise T... | 386 |
"""simple docstring"""
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ) -> Union[str, Any]:
'''simple docstring'''
_lowerCamelCase : ... | 386 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .t... | 594 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
... | 634 | 0 |
'''simple docstring'''
def a_ ( ) -> int:
return 1
def a_ ( _UpperCAmelCase : int ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def a_ ( _UpperCAmelCase : int ) -> int:
ret... | 721 |
'''simple docstring'''
import random
def a_ ( _UpperCAmelCase : list ,_UpperCAmelCase : List[Any] ) -> tuple:
__snake_case , __snake_case , __snake_case : int = [], [], []
for element in data:
if element... | 124 | 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,
ge... | 68 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
__A = logging.getLogger()
@unittest.skip('Temporarily disable the doc tests.' )
@require_torch
@r... | 68 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__lowercase )
class _UpperCamelCase ( __lowercase ):
"""simple docstring"""
snake_case_... | 720 |
"""simple docstring"""
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
A = logging.get_logger(__name__)
A = {
"""voc... | 147 | 0 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
UpperCamelCase_ = """__DUMMY_TRANSFORMERS_USER__"""
UpperCamelCase_ = """Dummy User"""
UpperCamelCase_ = """hf_hZEmnoO... | 256 |
'''simple docstring'''
def UpperCAmelCase__ ( UpperCAmelCase_ : int = 10_00 ) -> int:
__lowerCamelCase : Union[str, Any] = 3
__lowerCamelCase : Dict = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
... | 13 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> bool:
"""simple docstring"""
if not isinstance(lowercase_ , lowercase_ ):
raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
if len(lowercase_ ) == 0:
raise ValueError('''... | 375 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
a_ = logging.get_logger(__name__)
a_ = {
"speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
# See all M-CTC-T models at https://huggingface.co/models?... | 375 | 1 |
'''simple docstring'''
def snake_case_ (UpperCamelCase : int ):
'''simple docstring'''
if not isinstance(UpperCamelCase , UpperCamelCase ):
raise TypeError('''only integers accepted as input''' )
else:
_a = ... | 22 | '''simple docstring'''
from random import randint, random
def lowerCAmelCase ( UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : bool = False , UpperCamelCase__ : bool = False , Up... | 262 | 0 |
'''simple docstring'''
from collections.abc import Iterable
from typing import Generic, TypeVar
a_ = TypeVar('_T')
class __SCREAMING_SNAKE_CASE ( Generic[_T] ):
def __init__( self : List[Any] , __lowercase : Iterable[_T] | None = Non... | 711 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json',
# See all GPTNeoX models at htt... | 665 | 0 |
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_vision_available():
... | 562 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCAmelCase : str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNot... | 46 | 0 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_util... | 713 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCAmelCase ( _A ):
SCREAMING_SNAKE_CASE_ : Tuple = (DDPMScheduler,)
def A ( s... | 141 | 0 |
"""simple docstring"""
import numpy as np
_a = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", ""... | 19 |
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,
Ber... | 70 | 0 |
"""simple docstring"""
__A : Tuple = '\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github... | 281 |
"""simple docstring"""
def snake_case__ ( _lowerCamelCase, _lowerCamelCase ) ->int:
"""simple docstring"""
return abs(_lowerCamelCase ) if a == 0 else greatest_common_divisor(b % a, _lowerCamelCase )
def snake_case__ ( _lowerCamelCase, _lowerCamelCa... | 281 | 1 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def UpperC... | 15 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def UpperCamelCase ( __magic_name__ : Dict , __magic_name__ : List[str]=7 ) -> Dict:
"""simple docstring"""
lowercase__ = ... | 15 | 1 |
'''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 imp... | 718 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
fro... | 338 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def UpperCamelCase ( SCREAMING_SNAKE_CASE_ ) ->Optional[int]:
if "model" in orig_key:
_lowerCamelCase : List[str] = orig_key.replace('''model... | 434 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase : Any = {
"""configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """C... | 444 | 0 |
import cva
import numpy as np
class _lowerCamelCase :
"""simple docstring"""
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE )->Any:
'''simple docstring'''
if k in (0.0_4, 0.0_6):
A_ : Tuple = k
... | 704 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class... | 152 | 0 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list[float] ):
if len(_UpperCAmelCase ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
if any(i <= 0 for i in nums ):
raise ValueError('All values... | 4 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class A_ ( SCREAMING_SNAKE_CASE ):
_UpperCAmelCase : int = (UnCLIPScheduler,)
def lowerCAmelCase ( self : Union[str, Any] ,**SCREAMI... | 652 | 0 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> --key_path... | 177 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDetection
fr... | 177 | 1 |
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
lowerCamelCase__ : Optional[Any] = {
"""sample_size""": 3_2,
"""in_channels""": 3,
"""out_channels""": 3,
"""layers_per_bl... | 12 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPipeline,
U... | 587 | 0 |
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_form... | 75 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Optional[Any] = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
class _SCRE... | 75 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"vocab_file": "vocab.json",
"merges_file": ... | 45 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class __A ( A_ ):
'''simple docstring'''
lowerCAmelCase : int = (UnCLIPScheduler,)
de... | 560 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : Dict = logging.get_logger(__name__)
A_ : Dict = {
'kssteven/ibert-robert... | 711 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import f... | 696 | 0 |
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 ...modeling_utils import P... | 351 | import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class A ( UpperCAmelCase_ , unittest.TestCase ):
__UpperCAmelCase : int = DownBlockaD #... | 486 | 0 |
import math
import sys
def __lowerCAmelCase ( UpperCamelCase ) -> int:
if number != int(UpperCamelCase ):
raise ValueError('''the value of input must be a natural number''' )
if number < 0:
raise ValueError('''the value of input must not be a negative number''' )
... | 470 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ = {
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
if not is_torch_available():
raise OptionalDependen... | 470 | 1 |
from __future__ import annotations
from collections.abc import Callable
def __lowercase ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = 100 , ) -> float:
'''simple docstring'''
__lowercase = x_start
__lowercase = fnc(_UpperCAmelCase )
... | 321 | from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTes... | 321 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelin... | 721 |
'''simple docstring'''
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
"""split_dict""" , [
SplitDict(),
SplitDict({"""train""": SplitInfo(name="""train""" , num_bytes=1_3_3_7 ... | 385 | 0 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data ... | 636 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase ( __UpperCamelCase = "isbn/0140328726" ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = olid.strip().... | 65 | 0 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .t... | 555 |
'''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 A ( A_ : str ):
snake_case : List[str] = int(A_ ... | 555 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class UpperCamelCase__ ( _lowerCAmelCase ):
"""simple docstring"""... | 104 |
"""simple docstring"""
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
f... | 104 | 1 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
a = logging.get_logger(__name__)
a = {name: getattr(transformers, name + "F... | 703 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
__SCREAMING_SNAKE_CAS... | 13 | 0 |
'''simple docstring'''
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings('ignore', category=UserWarning, module='torch.optim.lr_scheduler')
class lowerca... | 447 |
'''simple docstring'''
def lowerCamelCase__ ( SCREAMING_SNAKE_CASE : int = 1000 ):
UpperCAmelCase = -1
UpperCAmelCase = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
UpperCAmelCase = (n * n... | 447 | 1 |
class UpperCAmelCase_ ( __lowercase ):
pass
class UpperCAmelCase_ ( __lowercase ):
pass
class UpperCAmelCase_ :
def __init__( self : Dict ) -> Optional[int]:
lowerCAmelCase = [
[],
[],
... | 706 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case =logging.get_logger(__name__)
__snake_case ={
"""vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
# See a... | 513 | 0 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
_snake_case = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["export", "validate_model_out... | 500 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : str = [0 for i in range(r + 1 )]
# nc0 = 1
_lowerCAmelCase : Optional[int] = 1
for i in range(1 , n + 1 ):
... | 500 | 1 |
'''simple docstring'''
# Imports
import numpy as np
class _SCREAMING_SNAKE_CASE :
def __init__( self : Optional[int] , __UpperCamelCase : List[str]=None , __UpperCamelCase : Any=None , __UpperCamelCase : Dict=None , __UpperCamelCase : List[Any]=None , __UpperCa... | 574 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
Diffus... | 574 | 1 |
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis... | 291 |
from __future__ import annotations
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self :Dict , a :str , a :str ) -> Union[str, Any]:
__UpperCamelCase , __UpperCamelCase : Optional[int] = text, pattern
__... | 557 | 0 |
from functools import lru_cache
@lru_cache
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doctest.testmod()
... | 711 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
return getitem, k
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return setitem, k, v... | 152 | 0 |
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
from diffusers.ut... | 272 |
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_tokeni... | 106 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checko... | 96 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
fro... | 96 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A__ )
class _a ( A__ ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output ... | 185 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import requ... | 228 | 0 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
__lowerCamelCase = logging.getLogger(__name__)
class snake_case_ (a__ ):
"""simple docstring"""
def __init__( ... | 716 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class snake_case_ (TensorFormatte... | 455 | 0 |
'''simple docstring'''
def __lowerCamelCase ( __lowerCAmelCase : str ) -> str:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 369 |
import re
def lowerCAmelCase ( UpperCamelCase__ : str ) -> bool:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: Optional[int] = re.compile(
R'''^(?:0|94|\+94|0{2}94)''' R'''7(0|1|2|4|5|6|7|8)''' R'''(-| |)''' R'''\d{7}$''' )
return boo... | 202 | 0 |
from torch import nn
def _snake_case ( __snake_case ):
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f"""Unsupported activation function: {act_fn... | 71 | import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
AutoTokenizer,
... | 71 | 1 |
def __UpperCamelCase (_SCREAMING_SNAKE_CASE ) -> List[str]:
if num < 0:
return False
lowercase__ = num
lowercase__ = 0
while num > 0:
lowercase__ = rev_num * 10 + (num % 10)
num //= 10
return num_copy == rev_num
... | 235 |
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import... | 568 | 0 |
'''simple docstring'''
from collections.abc import Sequence
def __snake_case (__UpperCAmelCase , __UpperCAmelCase = False ):
"""simple docstring"""
if not arr:
return 0
lowerCamelCase_ : Dict = 0 if allow_empty_subarrays else float('''-inf''' )
lowerCamelC... | 418 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2... | 418 | 1 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 |
"""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 A( unittest.TestCase... | 355 | 0 |
from pathlib import Path
import fire
def SCREAMING_SNAKE_CASE__ ( lowerCAmelCase_ : str ,lowerCAmelCase_ : str ,lowerCAmelCase_ : int ) -> Optional[Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str =Path(lowerCA... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__SCREAMING_SNAKE_CASE = {
'configuration_efficientformer': [
'EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 153 | 0 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterMixin
... | 306 |
'''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_tokenizers... | 42 | 0 |
'''simple docstring'''
def lowerCAmelCase__ ( a_ : Optional[int] , a_ : List[Any] , a_ : Tuple , a_ : Optional[int] , a_ : List[Any] , a_ : Optional[Any] ) -> str:
if index == r:
for j in range(a_ ):
print(da... | 718 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase_ = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_available():
ra... | 599 | 0 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,... | 134 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
__UpperCam... | 266 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusion.modeling_roberta_series import (
... | 704 |
import math
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase=0 ) -> Tuple: # a graph with Node 0,1,...,N-1
lowerCAmelCase_ = n
lowerCAmelCase_ = [
[math.inf for j in range(0 , _UpperCamelCase )] for i ... | 279 | 0 |
'''simple docstring'''
from math import loga
def a__ ( lowerCAmelCase__ ) -> int:
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise TypeError('''Input value must b... | 75 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDe... | 63 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torc... | 106 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase : Dict = {
"configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "Mo... | 106 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, tor... | 9 | def _lowerCamelCase ( a_ : str):
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6'''))
def _lowerCamelCase ( a_ : str):
lowerCamelCase :Union[str, Any] = credit_card_number
lowerCamelCase :Tuple = 0
lowerC... | 166 | 0 |
import numpy as np
class lowerCAmelCase_ :
def __init__( self : Dict ):
lowerCAmelCase__ = (0, 0)
lowerCAmelCase__ = None
lowerCAmelCase__ = 0
lowerCAmelCase__ = 0
lowerCAmelCase__... | 288 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCAmelCase_ :
def __init__( self : Union[str, Any] , SCREAMING_SNAKE_CASE_ : Optional[Any] , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ):
... | 288 | 1 |
def a__ ( __UpperCamelCase , __UpperCamelCase = 0 ):
SCREAMING_SNAKE_CASE_ = length or len(__UpperCamelCase )
SCREAMING_SNAKE_CASE_ = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAK... | 140 |
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 DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import l... | 86 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attentio... | 717 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
__lowerCamelCase = re.compile(R'''\b(a|an|the)\b''', re.UNICODE)
__lowerCamelCase = None
def _a ( ):
a_ : Tuple = argparse.ArgumentParser("""Offi... | 478 | 0 |
from __future__ import annotations
def __snake_case ( _UpperCamelCase , _UpperCamelCase = None ) -> list[list[str]]:
_a = word_bank or []
# create a table
_a = len(_UpperCamelCase ) + 1
_a = []
for _ in range(_UpperCamelCase ):
table.append([] )
# se... | 487 |
def __snake_case ( _UpperCamelCase ) -> int:
_a = len(_UpperCamelCase )
_a = sum(_UpperCamelCase )
_a = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , n + 1 ):
_a = True
for i in range(1 , s + 1 ):
_a = F... | 487 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : Dict = np.shape(SCREAMING_SNAKE_CASE_ )
if rows != columns:
lowerCamelCase : ... | 702 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowercase_( SCREAMING_SNAKE_CASE_ = "isbn/0140328726" ):
'''simple docstring'''
lowerCamelCase : List[Any] = olid.strip().strip("/" ) # Remove leading... | 231 | 0 |
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