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 |
|---|---|---|---|---|
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
@flax... | 331 |
'''simple docstring'''
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
lowerCAmelCase :Tuple = (
'''4S 3H 2C 7S 5H''',
'''9D 8H 2C 6S 7H''',
'''2D 6D 9D TH 7D''',
'''TC 8C 2S JH 6C''',
'''JH 8S TH AH QH''',
'... | 331 | 1 |
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_up_block
... | 365 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Dict = logging.get_logger(__name__)
a : List[Any] = {
'''s-JoL/Open-Llama-V1''': '''https://huggingface.co/s-JoL/Open-Llama-V1/blob/mai... | 79 | 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 torch
... | 303 |
_a = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _a ( SCREAMING_SNAKE_CASE : int ) -> int:
"""simple docstring"""
__lowerCAmelCase: Optional[int] = 0
while number:
# Increased Speed Slightly by checking every ... | 322 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
ViTHybridC... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
... | 127 | 0 |
'''simple docstring'''
def __lowerCamelCase ( A__ = 1_000 ) -> int:
"""simple docstring"""
return sum(e for e in range(3 , __UpperCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f'''{solution() = }''')
| 28 |
"""simple docstring"""
import re
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
__A ... | 266 | 0 |
from datetime import datetime
import requests
def _A ( lowerCAmelCase_ : Dict ):
"""simple docstring"""
lowerCAmelCase__ = "https://downloadgram.net/wp-json/wppress/video-downloader/video?url="
lowerCAmelCase__ = requests.get(base_... | 356 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _A ( lowerCAmelCase_ : str , lowerCAmelCase_ : str , **lowerCAmelCase_ : str ):
"""simple docstring"""
lowerCAmelCase__ = AutoConfig... | 221 | 0 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_a... | 79 |
'''simple docstring'''
from __future__ import annotations
def __lowercase ( __lowercase , __lowercase = None , __lowercase = None ) -> None:
'''simple docstring'''
if start is None:
_A = 0
if end is None:
_A = len... | 79 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
"""CarlCochet/trajectory-transformer-halfcheetah-medium-v2""": (
"""https://huggingface.co/CarlCochet/trajectory-transforme... | 361 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ..... | 139 | 0 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
SCREAMING_SNAKE_CASE : List[str] = 6_378_137.0
SCREAMING_SNAKE_CASE : Tuple = 6_356_752.314_245
SCREAMING_SNAKE_CASE : Dict = 637_8137
def lowerc... | 102 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_co... | 79 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
f... | 358 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def A_ ( snake_case_ : str = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
UpperCamelCase : Any = BeautifulSoup(requests.get(snake_case_ ).text ,"""html.... | 27 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configur... | 134 |
from __future__ import annotations
_SCREAMING_SNAKE_CASE : Optional[int] = []
def UpperCAmelCase__ (UpperCamelCase_ ,UpperCamelCase_ ,UpperCamelCase_ ):
"""simple docstring"""
for i in range(len(UpperCamelCase_ ) ):
if board[ro... | 127 | 0 |
'''simple docstring'''
import os
def _lowerCAmelCase ( __snake_case : List[str] ) -> Optional[Any]:
__A : List[str] = len(grid[0] )
__A : List[Any] = len(__snake_case )
__A : int = 0
__... | 190 |
'''simple docstring'''
import math
def _lowerCAmelCase ( __snake_case : int ) -> bool:
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... | 190 | 1 |
'''simple docstring'''
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spect... | 67 | """simple docstring"""
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_avail... | 221 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {'''configuration_vit_msn''': ['''VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMSNConfig''']}
try:
if not is_torch_available():
raise OptionalDependencyN... | 103 |
import re
def UpperCamelCase ( snake_case__ : str ) -> 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... | 103 | 1 |
def lowerCAmelCase_ ( _lowercase : List[Any]) -> List[Any]:
"""simple docstring"""
if not isinstance(_lowercase , _lowercase):
a__ : Union[str, Any] = F'''Input value of [number={number}] must be an integer'''
raise TypeErro... | 170 |
'''simple docstring'''
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class _snake_... | 139 | 0 |
'''simple docstring'''
from math import factorial
class __UpperCamelCase :
def __init__( self , __a , __a ):
'''simple docstring'''
__a : List[str] = real
if isinstance(__a , __a ):
__a : int = [1] *... | 366 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
__lowercase : Optional[Any] = True
except (ImportError, ModuleNotFoundError):
__lowercase : Dict = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', quiet=True)
... | 294 | 0 |
import argparse
from collections import defaultdict
import yaml
__a = 'docs/source/en/_toctree.yml'
def a ( snake_case__: Dict ):
'''simple docstring'''
lowercase_ = defaultdict(snake_case__ )
for doc in model_doc:
counts[doc["... | 30 |
'''simple docstring'''
import requests
__lowercase : Tuple = '' # <-- Put your OpenWeatherMap appid here!
__lowercase : Tuple = 'https://api.openweathermap.org/data/2.5/'
def lowerCamelCase (_SCREAMING_SNAKE_CASE : str = "Chicago" , _SCREAMING_SNAKE_CASE ... | 27 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( a_: int, a_: int ):
if not isinstance(a_, a_ ):
raise ValueError("iterations must be defined as integers" )
if not isinstance(a_, a_ ) or not number >= 1:
raise ValueError(
"starting number must be\n ... | 17 | '''simple docstring'''
import baseaa
def __UpperCAmelCase ( a_: str ):
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCAmelCase ( a_: bytes ):
return baseaa.baadecode(a_ ).decode("utf-8" )
if __name__ == "__main__":
... | 17 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffus... | 190 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : List[str] = {
'''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''GitVisionConfi... | 190 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
UpperCamelCase_ = get_tests_dir('fixtures/test_... | 350 |
"""simple docstring"""
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->List[Any]:
"""simple docstring"""
a_ = {
"en": "Machine learning is great, isn't ... | 303 | 0 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def UpperCamelCase( __UpperCamelCase : Any ... | 103 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transfor... | 103 | 1 |
def _A ( snake_case ) -> list:
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(__UpperCAmelCase ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('doctest').testmod()
| 356 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
_snake_case = logging.get_logger(__name__)
class a__ ( lowerCamelCase_ ):
def __init__( self , *_UpperCamelCase , **_UpperCamelCa... | 199 | 0 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
"RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json",
}
cla... | 247 |
"""simple docstring"""
_snake_case = '\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.gi... | 294 | 0 |
import unittest
import numpy as np
from datasets import load_dataset
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_tor... | 360 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 143 | 0 |
"""simple docstring"""
def _A ( UpperCamelCase_ : int, UpperCamelCase_ : int) -> str:
'''simple docstring'''
if not isinstance(UpperCamelCase_, UpperCamelCase_):
raise ValueError("iterations must be defined as integers")
if not isinstance(UpperCamelCase_, Upper... | 17 |
"""simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
_a = '__DUMMY_TRANSFORMERS_USER__'
_a = 'Dummy User'
_a = 'hf_hZEmnoOEYISjraJtbySaKCNnSuYAvukaT... | 17 | 1 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a__ ( __SCREAMING_SNAKE_CASE ) -> int:
__lowerCAmelCase: Optional[int] = FileLock(str(tmpdir / "foo.lock" ) )
__lowerCAmelCase: List[str... | 108 |
"""simple docstring"""
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
if is_torch_available()... | 108 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowerCamelCase ( metaclass=lowerCAmelCase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['note_seq']
def __init__(self , *_lowerCamelCase , **_lowerCamelCase ):
"""simple do... | 171 |
def a__ ( snake_case = 1_000_000 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Union[str, Any] = 1
__SCREAMING_SNAKE_CASE : Optional[Any] = 1
__SCREAMING_SNAKE_CASE : Optional[int] = {1: 1}
for inputa in range(2 , snake_case ):
__SCREAMING_SNAKE... | 303 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_A = logging.get_logger(__name__)
_A = {"""vocab_file""": """vocab.json""", """... | 360 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class lowerCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__(self , _lowerCamelCase , _lowerCamelCase , _lower... | 166 | 0 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerCAmelCase__ = get_tests_dir(... | 68 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_u... | 199 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Dict = """▁"""
_lowercase : List[A... | 356 |
'''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
_lowercase : List[Any] = logging.get_logger(__nam... | 264 | 0 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import Auto... | 95 | import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class __snake_case ( unittest.TestCase ):
@require_torch
... | 143 | 0 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.nn as n... | 295 |
def lowerCamelCase__ ( UpperCamelCase__ : list[list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : list[int] ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
... | 295 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-... | 108 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-... | 108 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class UpperCamelCase_ ( UpperCame... | 195 |
"""simple docstring"""
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,
... | 195 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case : Optional[Any] = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerConfig... | 94 |
'''simple docstring'''
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
... | 166 | 0 |
def __lowerCamelCase ( snake_case__ ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def __lowerCamelCase ( snake_case__ ... | 364 |
import copy
import re
class __UpperCAmelCase :
__snake_case : Any = "hp"
__snake_case : str = {}
__snake_case : List[Any] = None
@classmethod
def UpperCamelCase ( cls: Optional[Any] ... | 125 | 0 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowercase__ : Optional[Any] = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
''... | 264 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : List[Any] = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/confi... | 264 | 1 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
lowercase : Optional[Any] = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
lowercase : Optional... | 225 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor,... | 225 | 1 |
from __future__ import annotations
def _lowerCamelCase( lowercase__ , lowercase__ ) -> Any:
'''simple docstring'''
if len(lowercase__ ) <= 1 or n <= 1:
return
insert_next(lowercase__ , n - 1 )
rec_insertion_sort(lowercase__ , n - 1 )
def _lowerCamelCase( lo... | 295 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer, DP... | 295 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.util... | 364 |
'''simple docstring'''
def __a ( UpperCAmelCase ) ->bool:
"""simple docstring"""
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def __a ( UpperCAmelCase ) ->bool:
"""simple docstring"""
A ... | 337 | 0 |
# 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 applicab... | 195 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimen... | 195 | 1 |
"""simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__SCREAMING_SNAKE_CASE : int = '__DUMMY_TRANSFORMERS_USER__'
__SCREAMING_SNAKE_CASE : List[Any] = ... | 352 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __A (snake_case__):
'''simple docstring'''
__lowercase: Any = ["""image_processor""", """tokenizer"""]
__lowercase... | 233 | 0 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_UpperCamelCase : Optional[int] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_versio... | 77 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Any = logging.get_logger(__name__)
snake_case_ : Dict = {
"weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.jso... | 125 | 0 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
A_ : int = mf_knapsack(i - 1 , SCREAMING_SNAKE_CASE , ... | 65 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_available()... | 65 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list:
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(__UpperCAmelCase ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('doctest').testmod() | 225 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 225 | 1 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_utils import ... | 365 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = 42
class ... | 349 | 0 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers.mod... | 36 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__a = {
'''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''],
'''tokenization_ctrl''': ['''CTRLTokenizer'''],
}
try:
if not ... | 337 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list[int] , snake_case__ : str ):
"""simple docstring"""
_snake_case : str = int(snake_case__ )
# Initialize Result
_snake_case : Dict = []
# Traverse through all denomin... | 132 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A_ = {
'''configuration_maskformer''': ['''MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MaskFormerConfig'''],
'''c... | 132 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impor... | 62 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generatio... | 233 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
"configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"]
}... | 300 |
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_available("goo... | 300 | 1 |
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCamelCase__ = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models... | 65 | import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied f... | 65 | 1 |
def __snake_case ( __UpperCamelCase : list[list[float]] ):
"""simple docstring"""
A_ = []
for data in source_data:
for i, el in enumerate(__UpperCamelCase ):
if len(__UpperCamelCase ) < i + 1:
data... | 367 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a :Dict = logging.get_logger(__name__)
__a :int = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json'
),
'goo... | 329 | 0 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def _A ( lowercase ):
"""simple docstring"""
a , a =np.shape(lowercase )
if rows != columns:
a =(
'''\'table\' has to be of square shaped array b... | 81 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils impo... | 349 | 0 |
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def snake_case_ ( *lowerCAmelCase_ : List[str] ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : Optional[Any] = list... | 306 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : str , lowerCAmelCase_ : str ):
__lowercase : Any = get_failure_array(lowerCAmelCase_ )
# 2) Step through text searching for pattern
__lowercase , __lowercase : Op... | 306 | 1 |
"""simple docstring"""
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def _lowercase ( __lowerCAmelCase = True , *__lowerCAmelCase , **__lowerCAmelCase ) -> int:
if not is_tqdm_avai... | 132 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mod... | 132 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterM... | 55 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
f... | 55 | 1 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, FlaxMTaFo... | 300 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ra... | 300 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> float:
'''simple docstring'''
if digit_amount > 0:
return round(number - int(_UpperCAmelCase ) , _UpperCAmelCase )
return number - int(_UpperCAmelCase )
if __name__ ==... | 351 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixi... | 83 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from... | 267 |
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_backbone_common import Back... | 329 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = ... | 228 |
'''simple docstring'''
from __future__ import annotations
class a__ :
'''simple docstring'''
def __init__( self , lowerCamelCase_ ) -> None:
lowerCAmelCase__ = order
# a_{0} ... a_{k}
... | 228 | 1 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ... | 306 |
def __lowerCamelCase ( snake_case__ ,snake_case__ ,snake_case__ ) -> list:
"""simple docstring"""
_SCREAMING_SNAKE_CASE = len(snake_case__ )
_SCREAMING_SNAKE_CASE = [[0] * n for i in range(snake_case__ )]
for i... | 306 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
... | 360 |
"""simple docstring"""
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils ... | 58 | 0 |
'''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLIComma... | 55 |
'''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 SPIECE_UNDERLINE, logging
a_ : Any = log... | 55 | 1 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_pa... | 356 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 282 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import I... | 43 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowercase__ :
def __init__( self : List[Any] ,lowerCamelCase__ : int ,lowerCamelCase__ : MutableSequence[float] ):
'''simple docstring'''
if len(l... | 83 | 0 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def lowercase__ ( )-> Union[str, Any]:
with offline(... | 183 |
'''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = prime_factors(__UpperCamelCase )
if is_square_free(__UpperCamelCase ):
... | 183 | 1 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
def __A ( __lowerCamelCase ... | 228 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Optional[Any] = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"Jukebo... | 228 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple... | 366 |
'''simple docstring'''
import enum
import shutil
import sys
UpperCAmelCase_ , UpperCAmelCase_ = shutil.get_terminal_size()
UpperCAmelCase_ = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class lowerCAmelCase_ ( enum.Enum ):
'''simple docstring'''
lowerCAme... | 61 | 0 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():... | 8 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase_ = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""": ... | 58 | 0 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def A (__A : str , __A : str = "cpu" , __A : Union[str, None] = None ) -> None:
"""simple docstring"""
UpperCAmelCase_ = ... | 356 |
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,
... | 7 | 0 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
_lowercase = logging.get_logger(__name__)
... | 74 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
else:
_lowerCamelCase ... | 282 | 0 |
"""simple docstring"""
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_ut... | 366 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms im... | 234 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : Optional[int] = logging.get_logger(__name_... | 183 |
"""simple docstring"""
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
_SCREAMING_SNAKE_CASE : Tuple = version.parse(importlib_metadata.version('''nltk'''))
if NLTK_VERSION >= versi... | 183 | 1 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class __lowercase ( lowerCAmelCase__ , unittest.TestCase ):
... | 217 |
'''simple docstring'''
from math import sqrt
def _lowerCAmelCase ( lowerCamelCase_ : int ):
__lowercase = 0
for i in range(1 , int(sqrt(lowerCamelCase_ ) + 1 ) ):
if n % i == 0 and i != sqrt(lowerCamelCase_ ):
total += i + n... | 217 | 1 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
A__ : Union[str, Any] = {
'''n_samples''': 64,
'''horizon''': 32,
'''num_inference_steps''': 20,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, does not use value network
... | 103 |
"""simple docstring"""
def __a ( __lowerCamelCase = 3, __lowerCamelCase = 7, __lowerCamelCase = 100_0000 ):
UpperCAmelCase_ : Dict = 0
UpperCAmelCase_ : List[Any] = 1
for current_denominator in range(1, limit + 1 ):
UpperCAmelCase_ : Dict ... | 61 | 0 |
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTeacher,
EfficientFormerI... | 118 |
def __lowercase ( a__ ) -> int:
__SCREAMING_SNAKE_CASE = [[0 for _ in range(a__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__SCREAMING_SNAKE_CASE = 1
for n in range(m + 1 ):
for k in range(1 ... | 118 | 1 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Union[str, Any] = ... | 95 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowercase_ = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def _snake_case( SCREAMING_SNAKE_CA... | 7 | 0 |
"""simple docstring"""
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
a : int = '''scheduler_... | 351 |
"""simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noq... | 79 | 0 |
'''simple docstring'''
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 Mask... | 23 |
'''simple docstring'''
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def __lowe... | 234 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
'roberta-base': 'https://hug... | 358 |
from math import isqrt
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :int ) -> list[int]:
__lowerCAmelCase : Tuple = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , SCREAMING_SNAKE_CASE , SCR... | 232 | 0 |
"""simple docstring"""
def a__ ( __SCREAMING_SNAKE_CASE = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
try:
__lowerCAmelCase: int = int(__SCREAMING_SNAKE_CASE )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
r... | 217 |
"""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_configurati... | 217 | 1 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
... | 157 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( UpperCAmelCase : float , UpperCAmelCase : float , UpperCAmelCase : float ):
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError(... | 157 | 1 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Array... | 118 | import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase (... | 118 | 1 |
"""simple docstring"""
class __a :
"""simple docstring"""
def __init__( self : List[str] ):
UpperCamelCase__ : dict[str, TrieNode] ={} # Mapping from char to TrieNode
UpperCamelCase__ : Union[str, Any] =False
def ... | 354 |
"""simple docstring"""
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention... | 157 | 0 |
def a__ ( A_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__magic_name__ = len(A_ )
__magic_name__ = max(A_ )
__magic_name__ = min(A_ )
# creat... | 88 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version impo... | 79 | 0 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_m... | 347 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCamelCase : int = {
"shi-labs/n... | 347 | 1 |
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 transformers.util... | 59 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
lowercase : Optional[int] = Path(__file__).resolve().parents[3] / 'src'
sys.path.insert(1, str(git_repo_path))
import dataclasses # ... | 232 | 0 |
'''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_lowercase : int =... | 91 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def lowerCamelCase__ ( ):
'''simple docstring'''
print('''Truth Table of NOR Gate:''' ... | 91 | 1 |
from __future__ import annotations
def _UpperCamelCase ( snake_case__, snake_case__ ) -> float:
__UpperCAmelCase : int = sorted(numsa + numsa )
__UpperCAmelCase , __UpperCAmelCase : List[Any] = divmod(len(snake_case__ ), 2 )
... | 157 | def _UpperCamelCase ( snake_case__ ) -> int:
__UpperCAmelCase : Union[str, Any] = abs(snake_case__ )
__UpperCAmelCase : Dict = 0
while n > 0:
res += n % 10
n //= 10
return res
def _UpperCamelCas... | 157 | 1 |
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTokenizer, HfArgumentParser, ... | 304 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
lowerCAmelCase = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''albert-large-v1''': '''https://huggingface... | 304 | 1 |
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
lowerCamelCase__ = (
"""This metric will be removed from the library soon, metrics sh... | 302 | import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIF... | 157 | 0 |
import argparse
import datetime
import io
import itertools
import json
import math
import os
import platform
import re
import shlex
import subprocess
import sys
from pathlib import Path
from statistics import fmean
import pandas as pd
import torch
from tqdm import tqdm
import transformers
A : Tuple ... | 352 |
"""simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
A : ... | 259 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_att... | 347 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __A (metaclass=snake_case__):
'''simple docstring'''
__lowercase: List[Any] = ["""sentencepiece"""]
def __init__( self : int , *UpperCAmelCase_ : Any ... | 347 | 1 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def _snake_case ( _SCREAMING_SNAKE_CASE : str = "laptop" ) -> DataFrame:
"""simple docstring"""
lowerCAmelCase ... | 187 |
'''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
... | 187 | 1 |
"""simple docstring"""
from math import factorial
def _A (__a = 20 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
SCREAMING_SNAKE_CASE_ ... | 91 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : str):
'''simple docstring'''
... | 91 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
... | 351 |
"""simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
UpperCamelCase_ =0b1_0_1_1_0_0_1_1_1_1_... | 128 | 0 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_par... | 225 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMaskedLM,
DistilBer... | 303 | 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,
... | 352 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_u... | 220 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_a = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
try:
if not is_torc... | 61 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 259 | 0 |
'''simple docstring'''
from math import pow
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ , ):
'''simple docstring'''
if current_sum == needed_sum:
# If the sum of the powers is equ... | 362 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availa... | 311 | 0 |
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