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'''
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 A__ ( snake_case_ ):
def __init__( self : Tup... | 405 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ = {
'configuration_pix2struct': [
'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Pix2StructConfig',
'Pix2StructTextConfig',
'Pix2S... | 417 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Any = logging.get_logger(__name__)
__snake_case : Union[str, Any] = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingf... | 713 |
"""simple docstring"""
import string
from math import logaa
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase : int = document.translate(
str.maketrans("" ,"" ,string.punctuation ) ).replace("\n" ,"" )
... | 615 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
'configuration_roformer': ['ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP... | 300 |
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.image_processor import VaeImageProcessor
from diffusers.pipel... | 300 | 1 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> float:
"""simple docstring"""
def get_matched_characters(lowercase_ , lowercase_ ) -> str:
A__ = []
A__ = min(len(_stra ) , len(_stra ) ) // 2
... | 706 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
_lowerCamelCase : Optional[int] = namedtuple("""covid_data""", """cases deaths recovered""")
def SCREAMING_SNAKE_CASE ( lowercase_ = "https://www.worldometers.info/coronavirus/" ) -> covid_data... | 177 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def __snake_case ( _UpperCAmelCase : list[Any]):
create_state_space_tree(_UpperCAmelCase, [], 0)
def __snake_case ( _UpperCAmelCase : list[Any], _UpperCAmelCase ... | 212 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case_ : Optional[Any] = {
'configuration_blende... | 212 | 1 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 | 1 |
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowercase_ (A : Union[dict, list, tuple, torch.Tensor] ):
snake_case__ : ... | 478 |
from ....utils import logging
a_ :Optional[int] = logging.get_logger(__name__)
class snake_case__ ( lowerCAmelCase_ ):
"""simple docstring"""
def __init__( self : Optional[Any], _snake_case : List[str], _snake_case : Any=None, _snake_case : Tu... | 478 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
... | 718 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler... | 324 | 0 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sep... | 589 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : List[str] = {
"""configuration_distilbert""... | 589 | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_a : Optional[Any] = logging.get_logger(__name__)
... | 10 | '''simple docstring'''
def _lowercase ( lowerCamelCase__ , lowerCamelCase__ ) -> List[str]:
"""simple docstring"""
__UpperCAmelCase : Dict = (boundary[1] - boundary[0]) / steps
__UpperCAmelCase : Tuple = boundary[0... | 10 | 1 |
import colorsys
from PIL import Image # type: ignore
def a_ ( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
_lowerCamelCase : List[Any] =x
_lowerCamelCase ... | 464 |
"""simple docstring"""
def snake_case_ ( A_ : int, A_ : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def snake_case_ ( ):
'''simple docstring'''
print('''Truth Table of NOR Gate:''' )
print('''| I... | 83 | 0 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md""", """dataset_infos.j... | 719 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 322 | 0 |
# 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/LICENSE-2.0
#
# Unless required ... | 637 | from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_optuna,
... | 558 | 0 |
"""simple docstring"""
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 Opt... | 635 | """simple docstring"""
from __future__ import annotations
def lowerCamelCase_(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , )-> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supply more o... | 635 | 1 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase ( a__ ):
_UpperCAmelCase = (CMStochasticIterativeScheduler,)
_UpperCAmelCase = 10
... | 259 |
"""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 to... | 259 | 1 |
"""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_sequence_feature_extraction... | 721 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixi... | 468 | 0 |
UpperCAmelCase = {
0: '''0''',
1: '''1''',
2: '''2''',
3: '''3''',
4: '''4''',
5: '''5''',
6: '''6''',
7: '''7''',
8: '''8''',
9: '''9''',
10: '''a''',
11: '''b''',
12: '''c''',
13: '''d''',
14: '''e''',
15: '''f''',
}
def UpperCAmelCa... | 84 |
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 ..auto import CONFIG_MAPPING
__lowercase = logging.get_logger(__name__)
__lowercase ... | 203 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as j... | 659 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...sched... | 659 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCAmelCase__ : Optional[int] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies #... | 48 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner ... | 61 | 0 |
'''simple docstring'''
import unittest
from knapsack import knapsack as k
class snake_case_ ( unittest.TestCase ):
"""simple docstring"""
def __UpperCAmelCase ( self):
lowerCamelCase__ = 0
lowerCamelCase__ = [0]
lowe... | 426 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization i... | 426 | 1 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.ut... | 540 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _UpperCAmelCase ( a__ , a__ , a__):
'''simple docstring'''
a_ : List[Any] = 0
if start < end:
a_ : Dict = randint(a__ , a__)
a_ : List[str] ... | 540 | 1 |
"""simple docstring"""
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... | 538 | """simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
_A = ['small', 'medium', 'large']
_A = 'lm_head.decoder.weight'
_A = 'lm_head.weight'
def SCREAMING_SNAKE_CASE ( __UpperCAmelCase , ... | 538 | 1 |
'''simple docstring'''
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : Union[str, Any] = val
__A : Tuple = None
__A : Any = None... | 8 | """simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKIN... | 338 | 0 |
'''simple docstring'''
from __future__ import annotations
def _snake_case ( A_ : int | str ):
"""simple docstring"""
a_ : List[str] = str(A_ )
return n == n[::-1]
def _snake_case ( A_ : int = 100_0000 ):
... | 460 |
'''simple docstring'''
from math import factorial
__snake_case: List[Any] = {str(d): factorial(d) for d in range(10)}
def _snake_case ( A_ : int ):
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(A_ ) )
def _sna... | 460 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENE... | 48 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCondit... | 521 | 0 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
UpperCAmelCase = logging.getLogger()
... | 706 |
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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {"""vocab... | 351 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer
... | 340 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_snake_case = False
try:
_snake_case = _is_package_av... | 340 | 1 |
import math
def __lowerCAmelCase ( __magic_name__ , __magic_name__ ):
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(__magic_name__ )
else:
if x == 0: # 0 raised to any number is 0
return 0
elif y == 0:
return 1 # any nu... | 206 |
def __lowerCAmelCase ( __magic_name__ , __magic_name__ ):
return abs(__magic_name__ ) if a == 0 else greatest_common_divisor(b % a , __magic_name__ )
def __lowerCAmelCase ( __magic_name__ , __magic_name__ ):
while y: # --> when y=0 then loop will terminate and retu... | 206 | 1 |
'''simple docstring'''
from timeit import timeit
lowercase : str = {
'''MALAYALAM''': True,
'''String''': False,
'''rotor''': True,
'''level''': True,
'''A''': True,
'''BB''': True,
'''ABC''': False,
'''amanaplanacanalpanama''': True, # "a man a plan ... | 649 |
'''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 ImageProcessingSavingTestMixin, prepare... | 422 | 0 |
'''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration... | 653 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 584 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import... | 327 | 0 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils ... | 720 |
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_utils im... | 332 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A__ = {
'''configuration_roberta_prelayernorm''': [
'''ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARC... | 252 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
... | 574 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional import In... | 678 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def _SCREAMING_SNAKE_CASE ( snake_case_ : Tuple , snake_case_ : Union[str, Any] , snake_case_ : List[str] , snake_case_ : Union[str, Any] ):
__magic_name__ = {
'''en''': '''Machine learni... | 678 | 1 |
import math
def UpperCamelCase_( _snake_case : int = 100 ):
"""simple docstring"""
__a =sum(i * i for i in range(1 , n + 1 ) )
__a =int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return square_of_sum - sum_of_s... | 242 |
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
if is_torch_availabl... | 106 | 0 |
"""simple docstring"""
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : list , SCREAMING_SNAKE_CASE : list , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
lowerCAmelCase = len(SCREAMING_SNAKE_CASE )
lowerCAmelCase = [[0] ... | 702 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) !... | 393 | 0 |
"""simple docstring"""
import argparse
import os
import re
_a : Dict = """src/diffusers"""
# Pattern that looks at the indentation in a line.
_a : Union[str, Any] = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_a : Optional[Any] = ... | 213 | import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(""".""")
def lowerCAmelCase( __lowerCamelCase ):
__a = test_file.split(os.path.sep )
if components[0:2] != ["te... | 559 | 0 |
import math
class UpperCamelCase :
def __init__( self : List[str] , snake_case__ : Optional[int]=0 ): # a graph with Node 0,1,...,N-1
"""simple docstring"""
SCREAMING_SNAKE_CASE = n
SCREAMING_SNAKE_CASE = [
[math.inf for j in rang... | 673 |
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokeni... | 673 | 1 |
from __future__ import annotations
def lowerCamelCase_ ( _UpperCamelCase ) -> list[int]:
"""simple docstring"""
return [ord(_UpperCamelCase ) - 96 for elem in plain]
def lowerCamelCase_ ( _UpperCamelCase ) -> str:
"""simple docstring"""... | 60 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 11 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Tuple , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : float = 0 ):
... | 529 |
"""simple docstring"""
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface/autoformer-tourism-mont... | 529 | 1 |
from ....utils import logging
__lowerCAmelCase : Any =logging.get_logger(__name__)
class _lowercase ( A__ ):
'''simple docstring'''
def __init__( self :Any , lowerCAmelCase__ :List[str] , lowerCAmelCase__ :Any=None , lowerCAmelCase_... | 696 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : List[Any] =logging.get_logger(__name__)
__lowerCAmelCase : Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class _lowe... | 696 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
# See all Cvt models at https://hug... | 73 |
__magic_name__ = {
"joule": 1.0,
"kilojoule": 1_0_0_0,
"megajoule": 1_0_0_0_0_0_0,
"gigajoule": 1_0_0_0_0_0_0_0_0_0,
"wattsecond": 1.0,
"watthour": 3_6_0_0,
"kilowatthour": 3_6_0_0_0_0_0,
"newtonmeter": 1.0,
"calorie_nutr": 4_1_8_6.8,
"kilocalorie_nutr": ... | 73 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : str = logging.get_logger(__name__)
_lowercase : Tuple = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
cl... | 49 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowerCAmelCase_ : ... | 527 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ = {"p... | 539 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create sim... | 539 | 1 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
lowerCamel... | 381 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import... | 381 | 1 |
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
requir... | 702 | import cmath
import math
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> complex:
"""simple docstring"""
lowercase = math.radians(UpperCAmelCase )
lowercase = math.radians(UpperCAme... | 479 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
... | 169 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _snake_case (__lowercase , __lowercase , __lowercase):
# Initialise PyTorch model
Upp... | 23 | 0 |
"""simple docstring"""
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
... | 719 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def lowerCAmelCase_ ( UpperCamelCase__ : str ):
"""simple docstring"""
def decorator(UpperCamelCase__ : Tuple ):
__lowercase = getattr(UpperCamelCase__ , """han... | 442 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import ... | 53 |
# 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 app... | 53 | 1 |
import string
from math import logaa
def _A ( A__ , A__ ):
"""simple docstring"""
__lowercase = document.translate(
str.maketrans('''''' , '''''' , string.punctuation ) ).replace('''\n''' , '''''' )
__lowercase = document_witho... | 719 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def _A ( A__ , A__ , A__ , A__ , A__ ):
"""simple docstring"""
__lowercase = int(np.ceil((x_end - xa) / step_size ) )
__lowercase = np.zeros((n + 1,... | 624 | 0 |
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import torch
lowerCamelCase__ ... | 122 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __SCREAMING_SNAKE_CASE ( lower... | 700 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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 Toke... | 88 | 0 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class _snake_case :
def __init__( self : Optional[int] ,SCREAMING_SNAKE_CASE__ : list[tuple[float, float]] ):
SCREAMING_SNAKE_CASE:List[Any] = lis... | 143 |
"""simple docstring"""
from __future__ import annotations
import math
class lowerCAmelCase__ :
def __init__( self : int , _lowerCamelCase : int ):
_snake_case = size
# approximate the overall size of segment tree with given valu... | 224 | 0 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
lowercase : List[Any] = TypeVar("""T""")
def UpperCAmelCase_ ( _UpperCAmelCase ):
return (position - 1) // 2
def UpperCAmelCase_ ( _UpperCAmelCase ):
... | 584 | from __future__ import annotations
import os
from collections.abc import Mapping
lowercase : str = tuple[int, int]
class a__ :
def __init__( self : Optional[Any] , A_ : set[int] , A_ : Mapping[EdgeT, int] ) -> N... | 584 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
A_ = 42
A_ = 42
class SCREAMING_SNAKE_CASE ... | 484 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A = {
'configuration_mobilebert': [
'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileBertConf... | 484 | 1 |
class lowercase_ :
def __init__( self , __A ) -> List[Any]:
SCREAMING_SNAKE_CASE_ : int =val
SCREAMING_SNAKE_CASE_ : Optional[Any] =None
SCREAMING_SNAKE_CASE_ : str =None
def _snake_case ... | 711 |
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : str ) -> str:
return " ".join(
''''''.join(word[::-1] ) if len(UpperCAmelCase_ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_... | 431 | 0 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if not all(x.isalpha() for x in string ):
raise ValueError("""String must only contain alphabetic characters.""" )
UpperCAmelCase__ : List[Any] = sorted(string.lowe... | 65 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tenso... | 65 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
def _lowerCamelCase ( UpperCAmelCase_ : float, UpperCAmelCase_ : float, UpperCAmelCase_ : float ) -> tuple:
"""simple docstring"""
... | 704 |
"""simple docstring"""
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class UpperCamelCase__ :
"""simple docstri... | 562 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a: Optional[Any] = {'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except Opti... | 108 |
'''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 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 612 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_mo... | 612 | 1 |
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepa... | 43 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_com... | 259 | 0 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import Paddi... | 700 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_sa... | 226 | 0 |
'''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 transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import... | 94 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
def A__ ( self : Optional[int] ) -> List[str]:
'''simple docstr... | 94 | 1 |
__snake_case :Optional[int] ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case :Tuple ... | 224 |
__snake_case :List[Any] =range(2, 20 + 1)
__snake_case :Dict =[10**k for k in range(ks[-1] + 1)]
__snake_case :dict[int, dict[int, list[list[int]]]] ={}
def lowerCamelCase_ ( lowerCAmelCase__ : List[Any] , lowerCAmelCase__ : Union[str, Any] , lowerCAmelCase__ : Dict , lo... | 224 | 1 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> None:
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and ar... | 228 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
_lowerCamelCase : List[str] = """\
"""
_lowerCamelCase : Optional[int] = """
Perplexity (PPL... | 352 | 0 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase__ : List[Any] = logging.get_logger(__name__)
class _UpperCamelCase ( A_ ):
'''simple docstring'''
def __init__( ... | 486 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def A_( A ):
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output , args.config , args.finetuning_... | 486 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
def lowerCAmelCase_ ( snake_case_ : float , snake_case_ : float , snake_case_ : float ) -> tuple:
'''simple docstring'''
UpperCAmelCase_ ... | 78 | '''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 78 | 1 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
get_... | 107 | import re
def A__ ( snake_case_ : str ):
if len(re.findall('''[ATCG]''' , snake_case_ ) ) != len(snake_case_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '''TAGC''' ) )
if __name__ == "__main__":
... | 107 | 1 |
"""simple docstring"""
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from dif... | 602 | from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class SCREAMING_SNAKE_CASE_ ( nn.Module ):
'''simple docstring'''
def __init__( self : Union[str, Any] , SCREAMING_SNAKE_CASE__ : ... | 305 | 0 |
# 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... | 718 |
def SCREAMING_SNAKE_CASE ( lowerCAmelCase ):
_UpperCamelCase = []
if len(lowerCAmelCase ) == 1:
return [nums.copy()]
for _ in range(len(lowerCAmelCase ) ):
_UpperCamelCase = nums.pop(0 )
... | 105 | 0 |
'''simple docstring'''
def UpperCAmelCase_ ( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ ):
"""simple docstring"""
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
lowerCAmelCase__ : Tuple = mf_knapsack(i... | 378 |
'''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
snake_case = logging.get_logger(__name__)
snake_case = {
""... | 378 | 1 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_util... | 718 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():
... | 81 | 0 |
"""simple docstring"""
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from ... | 630 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterM... | 158 | 0 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nic... | 716 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 0 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''nielsr/canine-s''': 2_0_4_8,
}
# Unicode defines 1,114,112 total “codepoints... | 250 |
'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__n... | 539 | 0 |
# Copyright (c) 2021-, NVIDIA CORPORATION. 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 ... | 290 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onn... | 290 | 1 |
# 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 lowerCamelCase ( ... | 579 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class lowerCamelCase ( lowercase__ ):
'''simple docstring'''
def __init__( self , *lowerCAmel... | 579 | 1 |
'''simple docstring'''
def lowercase ( lowerCAmelCase : Optional[Any]):
"""simple docstring"""
_A : List[Any] = [1]
_A : Union[str, Any] = 0, 0, 0
_A : Optional[int] = ugly_nums[ia] * 2
_A : Any = ugly_nums[ia] *... | 711 |
'''simple docstring'''
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def lowercase ( lowerCAmelCase : str , lowerCAmelCase : Optional[int] , lowerCAmelCase : Any , lowerCAmelCase : List[str]... | 417 | 0 |
import pytest
import datasets
# Import fixture modules as plugins
__snake_case = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def _A ( _lowercase , _lowercase ) -> Tuple:
"""simple docstring"""
for item in ... | 1 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( snake_case , snake_case ) -> list[tuple[int, int]]:
__lowercase , __lowercase = position
__lowercase = [
(y + 1, x + 2),
(y - 1, x + 2),
(y + 1, x - 2),
(y -... | 375 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .em... | 715 |
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 is_torch_avail... | 73 | 0 |
class lowercase_ :
def __init__( self) -> str:
a__ =0
a__ =0
a__ ={}
def __UpperCamelCase ( self , lowercase_) -> Dict:
if vertex not in self.adjacency:
a__ ={}
self... | 20 | """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
__lowerCAmelCase : List[str] =logging.get_logg... | 359 | 0 |
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 import (
AutoTokeni... | 639 |
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditionalGeneration, BartTokeniz... | 639 | 1 |
'''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
_UpperCamelCase : Dict = get_tests_dir("fixtur... | 284 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_UpperCamelCase : str = {
"configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeo... | 284 | 1 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface i... | 161 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase_ = logging.get_logger(__name__)
def UpperCamelCase( lowercase_ , lowercase_ ... | 161 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( a_: int ):
if n == 1 or not isinstance(a_, a_ ):
return 0
elif n == 2:
return 1
else:
_UpperCAmelCase : Dict = [0, 1]
for i in range(2, n + 1 ):
sequence.append(sequence[i - 1] + sequence[i ... | 494 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json',
}
class A__ ... | 494 | 1 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase_ : Tuple = False... | 710 |
"""simple docstring"""
def UpperCAmelCase__ ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase=False ):
"""simple docstring"""
if isinstance(_UpperCAmelCase , _UpperCAmelCase ) and isinstance(_UpperCAmelCase , _UpperCAmelCase ):
A_ :... | 302 | 0 |
'''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
... | 508 |
'''simple docstring'''
from math import isqrt
def __snake_case ( lowercase : int ):
snake_case_ = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
... | 508 | 1 |
import argparse
import os
import re
import packaging.version
UpperCAmelCase_ = 'examples/'
UpperCAmelCase_ = {
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"... | 369 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
UpperCAmelCase_ = False
class lowercase__ ( u... | 369 | 1 |
"""simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _lowerCamelCase ( UpperCAmelCase_ : str, UpperCAmelCase_ : complex, UpperCAmelCase_ : str = "x", UpperCAmelCase_ : float = 10**-10, UpperCAme... | 104 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_utils import e... | 593 | 0 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
... | 702 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class _A ( unittest.TestCase ):
... | 469 | 0 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class A__ ( unittest.TestCase ):
def snake_case_ ... | 288 |
'''simple docstring'''
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""", [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize("""input_in_memory_max_size""", ["""default""", 0, 1_00 * 2**20, 9_00 * ... | 288 | 1 |
from __future__ import annotations
def _a ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ):
a_ : Any = list(range(len(__UpperCamelCase ) ) )
a_ : Union[str, Any] = [v / w for v, w in zip(__UpperCamelCase , __UpperCamelCase )]
index.sort(... | 478 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__lowerCamelCase = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and must be sm... | 478 | 1 |
def lowercase__ ( A_: Tuple ) -> str:
"""simple docstring"""
__UpperCAmelCase =len(A_ )
__UpperCAmelCase =sum(A_ )
__UpperCAmelCase =[[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , n ... | 68 |
def __lowerCAmelCase ( _UpperCamelCase = 1000000 ) -> int:
'''simple docstring'''
lowerCamelCase__: Optional[int] = set(range(3 , _UpperCamelCase , 2 ) )
primes.add(2 )
for p in range(3 , _UpperCamelCase , ... | 306 | 0 |
"""simple docstring"""
import numpy as np
from PIL import Image
def _snake_case ( snake_case__ : np.ndarray , snake_case__ : int , snake_case__ : int ):
A = np.array(snake_case__ )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is ... | 717 |
"""simple docstring"""
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
_lowercase =... | 22 | 0 |
'''simple docstring'''
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a_ = get_te... | 296 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team and The OpenBMB 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... | 296 | 1 |
'''simple docstring'''
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_ti... | 665 |
'''simple docstring'''
def _a( UpperCamelCase__ : str, UpperCamelCase__ : str ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Optional[int] =len(UpperCamelCase__ )
SCREAMING_SNAKE_CASE__ : Optional[Any] ... | 665 | 1 |
"""simple docstring"""
from math import sqrt
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
... | 657 |
"""simple docstring"""
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
return 10 - x * x
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
"""simple docstring"""
if equation(UpperCamelCase__ ) * equation(UpperCamelCase__ ) >= 0:
raise Val... | 657 | 1 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from tran... | 707 |
"""simple docstring"""
from __future__ import annotations
import requests
_a : List[str] = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_... | 87 | 0 |
from __future__ import annotations
import numpy as np
def A__ ( _a : np.ndarray ):
'''simple docstring'''
snake_case__ , snake_case__ : str =np.shape(_a )
if rows != columns:
snake_case__ : Any =(
"""'table' has to be of ... | 385 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator... | 385 | 1 |
'''simple docstring'''
def lowercase ( __magic_name__ , __magic_name__ , __magic_name__ ):
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
UpperCAmelCase : Tuple = _modexpt(__magic_name__ , ... | 609 |
'''simple docstring'''
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from... | 609 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.