code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
raise OptionalDependencyNotA... | 122 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Con... | 201 | 0 |
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 IMAGENET_DEFAULT_MEAN,... | 364 |
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 BatchFeatur... | 288 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A : Union[str, Any] = {
"configuration_altclip": [
"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 260 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__a = {"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerC... | 66 | 0 |
import datasets
from .evaluate import evaluate
__a = '''\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
booktitle={EMNLP},
year={2016}
}
'''
__a = '''
... | 173 |
from __future__ import annotations
from math import ceil, floor, sqrt
def __lowercase ( _UpperCamelCase = 2000000 ) ->int:
"""simple docstring"""
lowercase : list[int] = [0]
lowercase : int
for idx in range(1, ceil(sqrt(target * 2 ... | 173 | 1 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers.ut... | 101 |
'''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def a ( __a ) -> int:
'''simple docstring'''
for param in module.parameters():
UpperCamelCase__ :Dict = False
def a ( ) -> Union[str, Any]:
... | 97 | 0 |
"""simple docstring"""
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
__lowercase = [
'kernels/rwkv/wkv_cuda.cu',
'kernels/rwkv/wkv_op.cpp',
'kernels/deformable_detr/ms_deform_attn.h',
'kernels/deformable_detr/cud... | 359 | """simple docstring"""
def lowerCAmelCase (__UpperCamelCase : int = 1_0_0_0 ):
"""simple docstring"""
__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
... | 85 | 0 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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 require... | 196 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils imp... | 99 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
lowerCAmelCase : Optional[int] = {
"""sayakpaul/vit-msn-base""": """https://huggin... | 369 |
"""simple docstring"""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
lowerCAmel... | 168 | 0 |
'''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
UpperCamelCase__ = pytest.mark.integration
@pyt... | 181 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils impor... | 181 | 1 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require... | 305 | import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def a__ ( __UpperCamelCase ):
return x + 2
class lowerCamelCase (unittest.TestCase ):
"""simple docstring"""
def __A ( self : ... | 305 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
),
# See all TrOCR models at... | 36 | from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=_UpperCAmelCase ):
"""simple docstring"""
__a : Dict = ['''keras_nlp''']
def __init__( self , *lowerCAmelCase__ , **lowerCAmelCase__ ) -> Tuple:
'''si... | 210 | 0 |
import warnings
from functools import wraps
from typing import Callable
def UpperCAmelCase_ ( __UpperCAmelCase : Callable ) -> Callable:
@wraps(__UpperCAmelCase )
def _inner_fn(*__UpperCAmelCase : str , **__UpperCAmelCase : List[Any] ... | 353 |
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 tor... | 210 | 0 |
import qiskit
def lowerCamelCase__ ( a__ : int , a__ : int ) -> qiskit.result.counts.Counts:
UpperCamelCase_ = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
UpperCamelCase_ = qiskit.Q... | 122 |
from __future__ import annotations
def lowerCamelCase__ ( a__ : int | float | str , a__ : int | float | str ) -> list[str]:
if nth_term == "":
return [""]
UpperCamelCase_ = int(a__ )
UpperCamelCase_ = int(a__ )
U... | 122 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
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 i... | 242 |
'''simple docstring'''
from string import ascii_uppercase
lowercase ={str(ord(c) - 55): c for c in ascii_uppercase}
def lowerCamelCase__ ( __lowerCamelCase : int , __lowerCamelCase : int ):
'''simple docstring'''
if isinstance(__lowerCamelCase , __lo... | 242 | 1 |
'''simple docstring'''
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
... | 85 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
class snake_case__ (_UpperCamelCase ):
"""simple docstring"""
def __init__( self : Union[str, Any]... | 107 | 0 |
"""simple docstring"""
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
f... | 365 | """simple docstring"""
import unittest
from transformers import BertGenerationConfig, 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_modelin... | 321 | 0 |
'''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 impor... | 125 |
"""simple docstring"""
def lowercase ( _snake_case : int , _snake_case : int ) ->str:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
__snake_case : Tuple = str(bin(_snake_case ) ... | 102 | 0 |
'''simple docstring'''
def UpperCamelCase ( a ) -> list:
'''simple docstring'''
if len(a ) <= 1:
return [tuple(a )]
__magic_name__ = []
def generate(a , a ):
__magic_name__ = [0] * n
res.append(tu... | 98 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extractio... | 98 | 1 |
"""simple docstring"""
from collections.abc import Callable
def _snake_case ( _snake_case : Callable[[float], float] , _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
_A = a
_A ... | 315 |
import string
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> None:
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
A__ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 68 | 0 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE_ ( __a ):
"""simple docstring"""
__lowercase : Optional[int] = ['''image_processor''', '''tokenizer''']
... | 354 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ ):
while b:
__SCREAMING_SNAKE_CASE ,__SCREAMING_SNAKE_CASE = b, a % b
return a
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ ):
return a if b == 0 else euclidean_gcd_r... | 255 | 0 |
from __future__ import annotations
import queue
class __snake_case :
def __init__( self : Dict , _snake_case : Optional[int]):
"""simple docstring"""
UpperCAmelCase_ = data
UpperCAmelCase_ ... | 51 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ ... | 288 | 0 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transfor... | 229 |
'''simple docstring'''
import os
def A ():
with open(os.path.dirname(__lowerCamelCase ) + """/grid.txt""" ) as f:
_lowerCAmelCase = [] # noqa: E741
for _ in range(20 ):
l.append([int(__lowerCamelCase ) for x in f.readline().split()] )
... | 229 | 1 |
"""simple docstring"""
def __magic_name__ ( lowercase ):
SCREAMING_SNAKE_CASE_: Tuple =0
# if input_string is "aba" than new_input_string become "a|b|a"
SCREAMING_SNAKE_CASE_: str =""""""
SCREAMING_SNAKE_CASE_: Optional[int] =""""""
# append eac... | 173 |
"""simple docstring"""
def __magic_name__ ( lowercase , lowercase ):
SCREAMING_SNAKE_CASE_: Union[str, Any] =int(lowercase )
# Initialize Result
SCREAMING_SNAKE_CASE_: str =[]
# Traverse through all denomination
for denomination in reversed(l... | 173 | 1 |
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIterator
from tqdm import ... | 63 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {''... | 63 | 1 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common... | 51 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE : Optional[Any... | 85 | 0 |
'''simple docstring'''
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
_lowercase : str = importlib.util.find_spec("s3fs") is not None
... | 264 |
'''simple docstring'''
import qiskit
def snake_case_ ( __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
lowercase_ : List[Any] = qiskit.Aer.get_backend('''aer_simulator''' )
# Cre... | 264 | 1 |
"""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
fr... | 81 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
a_ : str = ... | 168 | 0 |
"""simple docstring"""
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def __a ( __lowerCamelCase, __lowerCamelCase = True, __lowerCamelCase = math.inf, __lowerCamelCase = -math.inf, __lowerCamelCase = math.inf, __lowerCamelCase = -math.inf, __lowe... | 363 |
"""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 ):
'''simple docstring'''
def Upp... | 23 | 0 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class... | 305 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 305 | 1 |
'''simple docstring'''
lowerCAmelCase__ : int = {
"""A""": """.-""", """B""": """-...""", """C""": """-.-.""", """D""": """-..""", """E""": """.""", """F""": """..-.""", """G""": """--.""",
"""H""": """....""", """I""": """..""", """J""": """.---""", """K""": """-.-""", """L""": """.-..""", ... | 351 |
'''simple docstring'''
def __UpperCamelCase ( _UpperCAmelCase ):
if p < 2:
raise ValueError("p should not be less than 2!" )
elif p == 2:
return True
__UpperCAmelCase : List[str] = 4
__UpperCAmelCase : int = (1 << p) - 1
for _ in range(p - ... | 37 | 0 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowerCAmelCase__ = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_... | 108 | import csv
import tweepy
# Twitter API credentials
__a : Union[str, Any] = """"""
__a : Union[str, Any] = """"""
__a : Union[str, Any] = """"""
__a : List[Any] = """"""
def UpperCAmelCase ( lowercase ):
"""simple docstring"""
__l... | 210 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__lowerCamelCase )
class a ( __lowerCamelCase ):
__lowerCAmelCase : str =... | 44 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
... | 44 | 1 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase ) -> bool:
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
lowerCAmelCase__ : Union[str, Any] = f"""Input value of [number={number}] must be an integer"""
raise TypeErro... | 242 |
"""simple docstring"""
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
_A = logging.get_logger(__name__)
class _lowerCamelCase :
def __init__( sel... | 242 | 1 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> str:
"""simple docstring"""
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 60 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE :Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE :Union[str, Any] = {
"""BridgeTower/bridgetow... | 60 | 1 |
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 ... | 339 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.co/microsoft/unisp... | 320 | 0 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenizerFast,
XLMR... | 138 |
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 .tokenization_xlnet import... | 138 | 1 |
"""simple docstring"""
from math import isqrt
def a_ ( lowerCamelCase ):
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCamelCase ) + 1 ) )
def a_ ( lowerCamelCase = 1_0**6 ):
UpperCAmelCase__ = 0
U... | 98 | """simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
lowerCAmelCase__ : Optional[int] = [
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight... | 98 | 1 |
class a :
def __init__( self :Optional[Any] ):
snake_case__ : str = ''''''
snake_case__ : Union[str, Any] = ''''''
snake_case__ : int = []
def __lowerCamelCase ( self :str ,__lowe... | 44 |
def _lowerCAmelCase ( __lowerCAmelCase ) -> int:
"""simple docstring"""
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
snake_case__ : List[str] = 1
snake_case__ : int = 1
while repunit:
snake_case__ : Dic... | 44 | 1 |
"""simple docstring"""
import comet # From: unbabel-comet
import torch
import datasets
lowerCAmelCase__ = datasets.logging.get_logger(__name__)
lowerCAmelCase__ = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavi... | 108 |
"""simple docstring"""
def lowercase__ ( _UpperCAmelCase ) -> None:
'''simple docstring'''
lowercase : Union[str, Any] = generate_pascal_triangle(_UpperCAmelCase )
for row_idx in range(_UpperCAmelCase ):
# Print left spaces
... | 255 | 0 |
"""simple docstring"""
__A = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
__A = [{"""type""": """code""", """content""": INSTALL_CONTENT}]
__A ... | 352 |
"""simple docstring"""
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def __A (_SCREAMING_SNAKE_CASE = "" ) ->dict[str, float]:
"""simple docstring"""
lowerCAmelCase__ :Optional[Any] = url or 'https://www.imdb.com/ch... | 254 | 0 |
'''simple docstring'''
class _lowercase :
'''simple docstring'''
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE__ : int ) -> Any:
__lowerCAmelCase = n
__lowerCAmelCase = [None] * self.n
__lowerCAmelCase ... | 229 | '''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def a ( self : int ) -> Optional[Any]:
return ... | 229 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__a :List[str] = TypeVar('T')
class _a ( Generic[T] ):
"""simple docstring"""
def __init__( self : Any , UpperCAmel... | 351 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__a :int = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__a :Any = [file for file in filepaths if file != file.lower... | 329 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 200 ) -> int:
_a = [1, 2, 5, 10, 20, 50, 100, 200]
_a = [0] * (pence + 1)
_a = 1 # base case: 1 way to make 0 pence
for coin in coins:
for i in range(lowercase , pence +... | 63 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : bytes ) -> str:
return "".join([hex(lowercase )[2:].zfill(2 ).upper() for byte in list(lowercase )] )
def _lowerCamelCase ( lowercase : str ) -> bytes:
# Check data validity, fol... | 63 | 1 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCamelCase__ : Optional[int] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
... | 210 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def UpperCAmelCase_ ( __UpperCAmelCase : Optional[int] ) -> int:
if not is_accelerate_available():
return method
SCREAMING_SNAKE_... | 210 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import TypedDict
class _UpperCAmelCase ( lowerCAmelCase__):
_lowerCAmelCase : str
_lowerCAmelCase : int
def __lowercase ( _a ):
if not isinstance(_a , _a ):
raise TypeError('''The p... | 264 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfor... | 264 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : list[list[int]], __snake_case : int, __snake_case : int, __snake_case : list[int] ) -> Tuple:
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
... | 367 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCamelCase :
'''simple docstring'''
def __init__( self : List[str] , lowerCAmelCase_ : int ) -> None:
'''simple docstring'''
A__ : Any =num... | 136 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase ={
"configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
"tokeniz... | 334 |
'''simple docstring'''
from manim import *
class SCREAMING_SNAKE_CASE( A__ ):
"""simple docstring"""
def A ( self : Union[str, Any] ) -> List[str]:
UpperCAmelCase : Optional[Any] = Rectangle(height=0.5 , widt... | 23 | 0 |
def __magic_name__ ( __a : list ):
'''simple docstring'''
UpperCamelCase__ = len(__a )
for _ in range(__a ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
UpperCamelCase__ , UpperCamelCas... | 178 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 178 | 1 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ... | 45 |
'''simple docstring'''
import os
import unicodedata
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 = logging.get_logger(__na... | 37 | 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 ..auto import CONFIG_MAPPING
snake_case : int = logging.get_logger(__name__)
snake_case ... | 41 |
from __future__ import annotations
snake_case : Optional[int] = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
class _snake_case :
def __init__( self , _a , ... | 41 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_... | 44 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Any ) -> List[Any]: # noqa: E741
_lowerCAmelCase : Optional[int] = len(_lowerCamelCase )
_lowerCAmelCase : str = 0
_lowerCAmelCase : Any = [0] * n
... | 44 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(U... | 243 |
'''simple docstring'''
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
a__ : List[str] = {
'nielsr/canine-s'... | 243 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
snake_case__ : Optional[Any] = logging.getLogger(__name__)
def _snake_case ( ):
lowerCAmelCase : Tuple = argparse.ArgumentParser(
... | 60 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def _snake_case ( _snake_case : list[list[float]] ):
lowerCAmelCase : str = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implement... | 60 | 1 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def a__ ( __SCREAMING_SNAKE_CASE = 8 ) -> str:
__lowerCAmelCase: int = ascii_letters + digits + punctuation
r... | 108 |
"""simple docstring"""
from __future__ import annotations
from math import pi
def a__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) -> dict[str, float]:
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError("One an... | 108 | 1 |
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 AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get... | 138 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
logging.se... | 138 | 1 |
'''simple docstring'''
def UpperCAmelCase ( lowerCamelCase_ :int ):
'''simple docstring'''
snake_case_ : str = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4)) | 8 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.ut... | 8 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_a : List[Any] = logging.get_logger(__name__)
_a : Optional[int] = {
... | 44 | """simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Optional[Any] ,_lowerCamelCase : int ) ... | 44 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not is_torch_available():
... | 357 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def lowerCamelCase__ ( ... | 29 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( _lowerCamelCase: str ):
__SCREAMING_SNAKE_CASE : str = """"""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def lowerCAmelCase_ ( _lowerCamelCase: st... | 112 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_t... | 254 | 0 |
'''simple docstring'''
import math
import sys
def _A (lowerCAmelCase__ :Union[str, Any] ) -> Optional[int]:
'''simple docstring'''
_a = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
... | 355 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import... | 104 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, log... | 324 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 0 |
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 lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_ ):
# Initialise PyTo... | 364 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ ):
create_state_space_tree(snake_case_,[],0,[0 for i in range(len(snake_case_ ) )] )
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_,):
if index == len(snake... | 343 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
s... | 210 | from decimal import Decimal, getcontext
from math import ceil, factorial
def UpperCAmelCase ( lowercase ):
"""simple docstring"""
if not isinstance(lowercase , lowercase ):
raise TypeError('''Undefined for non-integers''' )
elif precision < 1:
... | 210 | 1 |
"""simple docstring"""
from __future__ import annotations
_UpperCAmelCase : Optional[Any] = tuple[int, int, int]
_UpperCAmelCase : Dict = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
_UpperCAmelCase : List[str] = "ABCDEFGHI... | 365 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( lowerCAmelCase):
_a = (DDIMParallelScheduler,)
_a = (('''eta''', 0.0), ('''num_inference_steps''', 50))
def SCREAMING_SNAKE_CAS... | 158 | 0 |
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 transformers.configurat... | 14 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> list:
'''simple docstring'''
lowercase_ = len(__lowerCAmelCase )
lowercase_ = [[0] * n for i in range(__lowerCAme... | 136 | 0 |
def __lowercase ( a__ ) -> str:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 350 |
import os
def __lowercase ( a__ = "input.txt" ) -> int:
with open(os.path.join(os.path.dirname(a__ ) , a__ ) ) as input_file:
__SCREAMING_SNAKE_CASE = [
[int(a__ ) for element in line.split(',' )]... | 118 | 0 |
from collections import defaultdict
def __UpperCAmelCase ( a_ , a_):
snake_case_ = first_str.lower().strip()
snake_case_ = second_str.lower().strip()
# Remove whitespace
snake_case_ = first_str.replace(' ' , '')
s... | 178 |
lowercase = "\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
lowercase = [{"type": "code", "content": INSTALL_CONTENT}]
lowercase = {
... | 178 | 1 |
'''simple docstring'''
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> str:
return " ".join(
"""""".join(word[::-1] ) if len(UpperCAmelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
prin... | 101 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase = {
'''configuration_blenderbot''': [
... | 101 | 1 |
'''simple docstring'''
import heapq
import sys
import numpy as np
_A : Dict =tuple[int, int]
class _lowercase :
def __init__( self: List[str] ):
lowerCamelCase__ : List[str] = []
lowerCamelCase_... | 41 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome... | 41 | 1 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
blender... | 197 | from __future__ import annotations
import numpy as np
def lowerCAmelCase( __lowerCamelCase ):
return np.maximum(0 , __lowerCamelCase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 197 | 1 |
"""simple docstring"""
UpperCamelCase_ = '\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.co... | 243 |
"""simple docstring"""
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from tra... | 243 | 1 |
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Optional[int] , UpperCAmelCase : Dict ):
__lowerCamelCase : str = name
__lowerCamelCase : Dict = val
def __... | 354 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils im... | 64 | 0 |
"""simple docstring"""
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def a_... | 108 |
"""simple docstring"""
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from tran... | 108 | 1 |
"""simple docstring"""
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
_A = logging.get_logger(__name__)
class lowerCamelCase :
'''simple docstring'''
SCREAMING_SNAKE_CASE = None
... | 350 |
"""simple docstring"""
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = (DDIMParallelScheduler,)
SCREAMING_SNAKE_CASE = ... | 166 | 0 |
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ ):
snake_case_ = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4)) | 8 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ = {'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 8 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Any , lowerCamelCase__ : Optional[Any] ):
'''simple docstring'''
return round(float(moles / volume ) * nfactor )
def __lowerCamelCase ( lowerCamelCase_... | 361 |
import math
import tensorflow as tf
from packaging import version
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] ):
'''simple docstring'''
lowerCamelCase = tf.convert_to_tensor(lowerCamelCase__ )
lowerCamelCase = 0.5 * (1.0 + tf.math.... | 66 | 0 |
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
snake_case_ : Optional[int] = datasets.logging.get_logger(__name__)
snake_case_ : Tuple = "\\n@inproceedings{bleurt,\n title={BLEURT: Learning Robust Metrics for... | 51 |
__UpperCAmelCase = {
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': 'd... | 29 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
A : str = {'UserAgent': UserAgent().random}
def __lowerCAmelCase ( a__ ) -> dict:
__a = script.contents[0]
__a = j... | 33 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A : Optional[int] = {
'configuration_roberta': ['ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MA... | 33 | 1 |
def lowerCamelCase_ ( UpperCamelCase__ : Any ) -> int:
"""simple docstring"""
stooge(UpperCamelCase__ , 0 , len(UpperCamelCase__ ) - 1 )
return arr
def lowerCamelCase_ ( UpperCamelCase__ : Dict , ... | 90 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''facebook/... | 104 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_UpperCAmelCase : Optional[int] = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""... | 355 |
from __future__ import annotations
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = []
create_all_state(1 , UpperCamelCase__ , UpperCamelCase__ , [] , ... | 200 | 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... | 80 | import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_te... | 343 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_... | 366 |
'''simple docstring'''
from __future__ import annotations
import requests
def _A ( _lowerCAmelCase ):
"""simple docstring"""
__lowercase =f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(_lowerCAmelCase ).json()
... | 48 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( ) -> int:
_a : List[Any] =0
for i in range(1 ,1001 ):
total += i**i
return str(SCREAMING_SNAKE_CASE_ )[-10:]
if __name__ == "__main__":
print(solution())
| 276 |
'''simple docstring'''
import math
import unittest
def __a(SCREAMING_SNAKE_CASE_ : int ):
'''simple docstring'''
assert isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number <... | 158 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
... | 365 | '''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ... | 237 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
A : ... | 118 | 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 AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get_t... | 118 | 1 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def UpperCAmelCase__ ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with pytest.ra... | 357 |
from collections.abc import Iterable
from typing import Generic, TypeVar
_UpperCAmelCase : Any = TypeVar("_T")
class __lowerCAmelCase ( Generic[_T]):
def __init__( self: Union[str, Any] , _lowerCAmelCase: Iterable[_T] | None = None ):
lowercase ... | 158 | 0 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase__ :Dict = {
"<": operator.lt,
"<=": operator.le,
"==": operator.eq,
"!=": operator.ne,
">=": operator.ge,
">": operator.gt,
}
def UpperCamelCase ... | 101 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INPAIN... | 101 | 1 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class __snake_case( _UpperCAmelCase ... | 371 |
'''simple docstring'''
from __future__ import annotations
def _snake_case ( _SCREAMING_SNAKE_CASE : int | str ) -> bool:
"""simple docstring"""
lowerCAmelCase = str(_SCREAMING_SNAKE_CASE )
return n == n[::-1]
def _snake_c... | 187 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : Tuple =logging.get_logger(__name__)
__lowerCAmelCase : ... | 197 | """simple docstring"""
from __future__ import annotations
from typing import Any
class _A :
def __init__( self , __lowerCAmelCase = 6 ):
"""simple docstring"""
lowercase = None
lowercase ... | 197 | 1 |
"""simple docstring"""
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, requ... | 356 |
"""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.a... | 181 | 0 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
__UpperCamelCase = logging.get_logger(__name__)
class UpperCamelCase ( lowerCAmelCase__ ):
... | 69 |
"""simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def UpperCAmelCase__ (snake_case__ : Optional[int] , snake_case__ : Any=7 ):
"""simple docstring"""
_snake_case... | 64 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 368 |
import math
import random
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = False ):
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
UpperCamelCase = 0.02
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ... | 65 | 0 |
"""simple docstring"""
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
__UpperCAmelCase = TypeVar('T')
class _SCREAMING_SNAKE_CASE ( Generic[T] ):
UpperCAmelCase_ :deque[T] # Cache store of keys
... | 84 |
'''simple docstring'''
import numpy
# List of input, output pairs
lowerCamelCase = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowerCamelCase = (((515, 22, 13), 555), ((61, 35, 49), 150))
lowerCamelCase = [2, ... | 166 | 0 |
'''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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescal... | 363 |
'''simple docstring'''
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available()... | 346 | 0 |
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def lowerCamelCase__ ( ):
raise RuntimeError("CUDA out of memory.")
class _UpperCamelCase ( nn.Module ... | 76 |
"""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
from ...test_bac... | 66 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOn... | 357 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
def _A ( SCREAMING_SNAKE_CASE :... | 148 | 0 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor... | 33 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__A : str = argparse.ArgumentParser()
parser.add_ar... | 33 | 1 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoen... | 353 |
'''simple docstring'''
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiff... | 242 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTMSNConfig
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 Con... | 89 |
'''simple docstring'''
from typing import Any
class lowercase__ :
'''simple docstring'''
def __init__( self , __snake_case ):
_SCREAMING_SNAKE_CASE : Dict = data
_SCREAMING_SNAKE_CASE : Optional[int] = None
... | 200 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list[int] ):
"""simple docstring"""
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
_snake_case : Any = sum(snake_case__ ) / len(snake_case__ ) # Calcu... | 357 |
"""simple docstring"""
from __future__ import annotations
from math import gcd
def UpperCAmelCase__ (snake_case__ : int , snake_case__ : int = 2 , snake_case__ : int = 1 , snake_case__ : int = 3 , ):
"""simple docstring"""
if num < 2:
... | 132 | 0 |
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