code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def _lowercase( __a : int , __a : int ):
if number < 0 or shift_amount < 0:
raise ValueError('both inputs must be positive integers' )
a__ =str(bin(__a ) )
binary_number += "0" * shift_amount
return binary_number
def ... | 20 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase_ : List[str] = {
"tanreinama/GPTSAN-2.8B-spout_is_uniform": (
"https://huggingface.co/tanreinama... | 21 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
'''simple docstring'''
class A :
def __init__( self : int , lowerCAmelCase_ : Union[str, Any] , lowerCAmelCase_ : Dict , lowerCAmelCase_ : List[str] ) -> Dict:
"""simple docstring"""
... | 22 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
def _snake_case (__lowercase , __lowercase):
return int((input_a, input_a).count(0) != 0)
def _snake_case ():
assert nand_gate(0 , 0) == 1
assert nand_gate(0 , 1) == 1
assert nand_gate(1 , 0) == 1
assert nand_gate(1 , 1) == 0... | 23 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
'''simple docstring'''
UpperCAmelCase_ : List[Any] = {
0: '''0''',
1: '''1''',
2: '''2''',
3: '''3''',
4: '''4''',
5: '''5''',
6: '''6''',
7: '''7''',
8: '''8''',
9: '''9''',
1_0: '''a''',
1_1: '''b''',
1_2: '''c''',
1_3: '''d''',
1_4: '''e... | 24 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 0 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'kakaobrain/align-base': 'https://huggingface.co/kakaobrain/align-base/res... | 25 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
'''simple docstring'''
from __future__ import annotations
class _A :
def __init__( self : Optional[int] , __magic_name__ : list[list[int]] ) -> str:
"""simple docstring"""
__snake_case : str = TypeError(
... | 26 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
import math
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
_A = 0
_A = 0
while num > 0:
_A = num % 8
_A = octal + (remainder * math.floor(math.pow(10 ... | 27 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsComma... | 28 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResa... | 29 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
def lowerCamelCase__ ( _lowercase , _lowercase ):
'''simple docstring'''
return "\n".join(
f'''{number} * {i} = {number * i}''' for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_table(number=5, number_of_terms=10)) | 30 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_d... | 31 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision.transforms.functional... | 32 | """simple docstring"""
import unittest
import numpy as np
import requests
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
... | 644 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase ) -> bool:
snake_case__ = str(__lowerCAmelCase )
return n == n[::-1]
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase = 100_0000 ) -> Union[str, Any]:
snake_case__ = ... | 33 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
"""simple docstring"""
def __snake_case ( _lowercase = 100 ):
"""simple docstring"""
UpperCamelCase = set()
UpperCamelCase = 0
UpperCamelCase = n + 1 # maximum limit
for a in range(2 ,_lowercase ):
for b in range... | 34 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor import... | 35 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import 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_... | 644 | 0 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _A ( unittest.TestCase ):
'''sim... | 36 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
def UpperCamelCase_ ( __a ) -> "list[int]":
if upper_limit < 0:
raise ValueError("Limit for the Catalan sequence must be ≥ 0" )
a__ : List[str] = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
a__ : Optional[int] = 1
if upper_limit > 0... | 37 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
'''simple docstring'''
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def UpperCamelCase__ ( __magic_name__ : Optional[Any] ) -> str:
'''simple docstr... | 38 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_toke... | 644 | 0 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
lowerCAmelCase_ = logging.get_logger(__name__)
class snake_case_ ( __A ):
'''simple docstring'''
def __init__( self : int , *_Uppe... | 39 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__UpperCAmelCase = {
'''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXJapaneseConfig'''],
'''tokeniz... | 40 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#... | 41 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
... | 42 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase = {
'configuration_whisper': ['WHISPER_PRETRAINED_CONFIG_ARCHIVE_M... | 43 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import... | 44 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase_ ( unittest.TestCase ):
... | 45 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
"""simple docstring"""
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configu... | 46 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 0 |
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 import BertTokenizer
SCREAMING_SNAKE_CASE__ = logging.get_l... | 47 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
from ac... | 48 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
W... | 49 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
UpperCamelCase : Tuple = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
UpperCamelCase : str... | 50 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 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
#
... | 51 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test... | 52 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
import requests
_snake_case : Tuple = '' # <-- Put your OpenWeatherMap appid here!
_snake_case : Dict = 'https://api.openweathermap.org/data/2.5/'
def a_ ( lowerCAmelCase_ : str = "Chicago", lowerCAmelCase_ : str = APPID ):
return reque... | 53 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class A ( __lowercase ):
_snake_case ='''Wav2Vec... | 54 | """simple docstring"""
import unittest
import numpy as np
import requests
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
... | 644 | 0 |
from __future__ import annotations
import math
import random
from typing import Any
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : Tuple ):
__A = []
__A = 0
__A = 0
def UpperCamelCase_ ( self : Li... | 55 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table i... | 56 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : Dict = logging.get_logger(__name__)
A_ : int = {
'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json',
# Se... | 57 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import 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_... | 644 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__lowerCAmelCase : List[str] = {
'''configuration_m... | 58 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
__A = {
"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": "dataclasses",
"datasets... | 59 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class __lowerCAmelCase ( _a, unittest.TestCase ):
lowerCamelCa... | 60 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_toke... | 644 | 0 |
import fire
from utils import calculate_rouge, save_json
def _A ( lowerCAmelCase_ : List[Any] , lowerCAmelCase_ : Optional[Any] , lowerCAmelCase_ : int=None , **lowerCAmelCase_ : Dict ):
"""simple docstring"""
lowerCAmelCase__ = [x.... | 61 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tenso... | 62 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
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 : List[str] = logging.get_logger(__na... | 63 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 0 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
lowercase_ : Tuple = {
'n_samples': 6_4,
'horizon': 3_2,
'num_inference_steps': 2_0,
'n_guide_steps': 2, # can set to 0 for faster sampling, does not use value network
'scale_grad_by_st... | 64 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__UpperCAmelCase = '\\n\n'
__UpperCAmelCase = '\nPerplexity (PPL) is one of the m... | 65 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase = [
"good first issue",
"feature request",
"wip",
]
def __magic_name__ ( ) -> List[str]:
_lowercase : Union[str, Any] = Github(os.environ['GITHUB_TOKEN'] )
... | 66 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def SCREAMING_SNAKE_CASE__ ( snake_case__ :Tuple ) -> int:
_lowercase = args.pruning_method
_lowercase = args.threshold... | 67 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
def lowercase__ ( A_: list[list[int | float]] ) -> int:
"""simple docstring"""
__UpperCAmelCase =len(A_ )
__UpperCAmelCase =len(matrix[0] )
__UpperCAmelCase =min(A_ , A_ )
for row in range(A_ ):
# ... | 68 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 0 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMSche... | 69 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import... | 70 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead."""
)
... | 71 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
_UpperCAmelCase : Tuple = '''examples/'''
_UpperCAmelCase : Union[str, Any] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''':... | 72 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
import math
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = [True] * n
SCREAMING_SNAKE_CASE = False
SCREAMING_SNAKE_CASE = False
SCREAMING_SNAKE_CASE = True
for i in range(3 , int(n**0.5 + 1) , 2):
SCREAMING_SNA... | 73 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def a__ ( snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Any = SwinConfig(image_size=192 )
if "base... | 74 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 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-... | 75 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
a_ ... | 76 | """simple docstring"""
import unittest
import numpy as np
import requests
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
... | 644 | 0 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from ... | 77 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
SCREAMING_SNAKE_CASE_: Dict =generate_large_matrix()
SCREAMING_SNAKE_CASE_: List[... | 78 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_com... | 79 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import 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_... | 644 | 0 |
from collections import deque
class __UpperCamelCase :
def __init__( self : Union[str, Any] , _lowerCAmelCase : str , _lowerCAmelCase : int , _lowerCAmelCase : int ) -> None:
"""simple docstring"""
__lowercase = pr... | 80 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_in... | 81 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 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 = logging.get_logger(__name__)
lowerCamelCase = {
"""xlm-ml... | 82 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_toke... | 644 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 83 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
# 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 required by applicab... | 84 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_S... | 85 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a :Any = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise Option... | 86 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
from __future__ import annotations
from math import pow, sqrt
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ) -> dict[str, float]:
"""simple docstring"""
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueError... | 87 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
"""simple docstring"""
from math import ceil
def _snake_case ( __snake_case : int = 1001 ):
"""simple docstring"""
_lowerCamelCase : Dict = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
_lowerCamelCase : List[str] = 2 *... | 88 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
from typing import Any
def UpperCamelCase_( lowerCamelCase_ ) -> list[Any]:
if not input_list:
return []
_lowercase : Optional[Any] = [input_list.count(lowerCamelCase_ ) for value in input_list]
_lowercase : List[str] = max(lowerCamelCase_ ... | 89 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, 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... | 90 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 0 |
"""simple docstring"""
from math import factorial
def _snake_case ( snake_case__ : int , snake_case__ : int , snake_case__ : float ):
if successes > trials:
raise ValueError('successes must be lower or equal to trials' )
if trials < 0 or successes < 0:
raise ValueError('the fun... | 91 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( __magic_name__ : str ) -> str:
return "".join(chr(ord(__magic_name__ ) - 32 ) if '''a''' <= char <= '''z''' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
... | 92 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
"""simple docstring"""
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__A = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__A = [file for file in fil... | 93 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart i... | 94 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class UpperCam... | 95 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
"""simple docstring"""
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 96 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
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_torch_available():
... | 97 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import... | 98 | """simple docstring"""
import unittest
import numpy as np
import requests
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
... | 644 | 0 |
from __future__ import annotations
def a (lowerCAmelCase__ , lowerCAmelCase__ ):
__a = get_failure_array(lowerCAmelCase__ )
# 2) Step through text searching for pattern
__a , __a = 0, 0 # index into text, pattern
while i < len(lowerCAmelCase__ ):
if pat... | 99 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test_tokenization_common ... | 100 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
from __future__ import annotations
import math
from collections.abc import Callable
def a__ ( A__, A__, A__, A__ = 1_0_0, ):
SCREAMING_SNAKE_CASE_ : Tuple = x_start
SCREAMING_SNAKE_CASE_ : Dict = fnc(A__ )
SCREAMING_SNAKE_CAS... | 101 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import 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_... | 644 | 0 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers impor... | 102 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def snake_case ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> Union[str, Any]:
_snake_case = {
'''en''': '''Machine learning is grea... | 103 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformer... | 104 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_toke... | 644 | 0 |
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 (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmentation,
... | 105 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Dict =logging.get_logger(__name__)
class lowerCAmelCase__ ( _lowerCamelCase ):
A_ : List[str] = 'timm_backbone'
def __init__( self : Optional[Any]... | 106 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def _SCREAMING_SNAKE_CASE ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ):
_A = [0] * no_of_processes
_A = [0] * no_of_processes
... | 107 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 0 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( __snake_case , __snake_case , __snake_case ) -> float:
if days_between_payments <= 0:
raise ValueError("""days_between_payments must be > 0""" )
if daily_interest_rate < 0:
... | 108 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorc... | 109 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
requ... | 1 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> List[str]:
'''simple docstring'''
return " ".join(
''''''.join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
... | 640 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,... | 446 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : str ) -> Optional[int]:
"""simple docstring"""
__lowerCamelCase = 0
# if input_string is "aba" than new_input_string become "a|b|a"
__lowerCamelCase = ''
__lowerCamelCase =... | 469 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class _lowerCAmelCase ( __UpperCamelCase ):
def... | 178 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
import torch
from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool
if is_datasets_available():
from datasets import load_dataset
class _lowerCAmelCase ( __UpperCamelCase ):
... | 411 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
"""simple docstring"""
import sys
import turtle
def _a ( UpperCAmelCase__ , UpperCAmelCase__ ) -> Tuple:
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def _a ( UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , ) -> ... | 482 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
import numpy as np
def _a ( UpperCamelCase_ : List[Any] , UpperCamelCase_ : Dict , UpperCamelCase_ : Union[str, Any] , UpperCamelCase_ : str , UpperCamelCase_ : Tuple ) -> Union[str, Any]:
"""simple docstring"""
lowe... | 339 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
def UpperCAmelCase__ ( lowerCamelCase_ : Dict , lowerCamelCase_ : List[Any] , lowerCamelCase_ : str , lowerCamelCase_ : Optional[Any] ):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
... | 47 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
__A = logging.get_logger(__name__)
... | 593 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
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