code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
from collections import Counter
from random import random
class lowerCAmelCase :
'''simple docstring'''
def __init__( self :List[Any] ) -> Optional[int]:
"""simple docstrin... | 516 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : List[Any] = {
'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'],
}
try:
if not is_torch_available():
... | 516 | 1 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils impor... | 708 |
"""simple docstring"""
import operator
def _UpperCAmelCase ( __lowerCamelCase : list , __lowerCamelCase : bool = False , __lowerCamelCase : list | None = None ) -> list:
_snake_case = operator.lt if reverse else operator.gt
_snake_case = solutio... | 430 | 0 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
UpperCAmelCase__ = '''
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
'''
UpperCAmelCase__ = '''
Args:
predictio... | 277 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_... | 260 | 0 |
'''simple docstring'''
from collections.abc import Generator
def lowercase ( ):
"""simple docstring"""
_A , _A : int = 0, 1
while True:
_A , _A : Optional[Any] = b, a + b
yield b
def lowercase ( lowerCAmelCa... | 719 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase__ ( snake... | 417 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from ... | 13 |
"""simple docstring"""
__A : Optional[int] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
... | 499 | 0 |
'''simple docstring'''
from math import factorial, pi
def __UpperCAmelCase ( a_: float, a_: int = 30 ):
if not isinstance(a_, (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or float for theta" )
if not isinstance(a_, a_ ... | 257 | '''simple docstring'''
import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__a = logging.get_logger(__name__)
__a = '▁'
__a = {'vo... | 257 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_SCREAMING_SNAKE_CASE )
class SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE )... | 129 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tok... | 129 | 1 |
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
__SCREAMING_SNAKE_CASE : str ='''▁'''
__SCREAMING_SNAKE_CASE : Union[str, An... | 72 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
... | 72 | 1 |
import argparse
import json
import subprocess
def __A(lowerCAmelCase , lowerCAmelCase ) -> Optional[int]:
"""simple docstring"""
_UpperCamelCase = []
_UpperCamelCase = (
F'curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'
... | 612 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
_UpperCamelCase : ... | 341 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
W... | 341 | 1 |
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
__UpperCAmelCase = 0
__UpperCAmelCase = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
... | 40 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import ... | 214 | 0 |
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 UpperCAmelCase_ ( _A ):
'''simple docstring'''
d... | 76 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Tuple = logging.get_logger(__name__)
__lowerCAmelCase : Tuple = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolv... | 76 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerat... | 697 |
from PIL import Image
def _SCREAMING_SNAKE_CASE ( lowercase : Image ):
'''simple docstring'''
lowerCamelCase_ , lowerCamelCase_ = image.size
lowerCamelCase_ = 0
lowerCamelCase_ = image.load()
for i in ... | 70 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class SCREAMING_SNAKE_CASE__ ( unittest.Tes... | 258 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _A ( __lowercase ):
... | 258 | 1 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def A_ ( snake_case__ ) -> List[Any]:
_UpperCamelCase :Any = args.pruning_method
_UpperCamelCase :Any ... | 355 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ :str = logging.get_logger(__name__)
UpperCamelCase__ :Optional[int] = {
"""microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/c... | 355 | 1 |
"""simple docstring"""
a_ = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def a__ ( ) -> None:
_A = input("Enter message: " )
_A = input("Enter key [alphanumeric]: " )
_A = input("Encrypt/Decrypt [e/d]: " )
if mode.lower().startswith("e"... | 621 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def a__ ( __lowercase ) -> Optional[int]:
_A = [
"encoder.version",
"decoder.version",
"model.enco... | 621 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabl... | 360 |
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
SCREAMING_SNAKE_CASE__ = datasets.logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = "\\n@inproceedings{bleurt,\n title={BLEURT: Learning Robust Metrics for Text Generation},\... | 631 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( _lowercase : Tuple ) -> list[int]: # This function is recursive
__UpperCAmelCase: int = len(_lowercase )
# If the array contains only one element, we return it (it's the stop condition of
... | 719 | '''simple docstring'''
import numpy
# List of input, output pairs
SCREAMING_SNAKE_CASE_ = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
SCREAMING_SNAKE_CASE_ = (((5_15, 22, 13), 5_55), ((61, 35, 49), 1_50))
SCREAMING_SNAKE_CASE_ = ... | 466 | 0 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the confi... | 642 |
def lowercase ( _a ,_a ) -> str:
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers" )
UpperCAmelCase_: str = str(bin(_a ) )
binary_number += "0" * shift_amount
return binary_number
def lowercase ( _a ... | 137 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __A ( UpperCamelCase__ ):
a__ : Any = """ClapFeatureExtractor"""
a__ : Tuple = ("""RobertaTokenizer""", """RobertaTokenizerFast""")
def _... | 415 | '''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE_: Union[str, Any] =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_: Optional[Any] ={
'ut/deta': 'https://huggingface.co/u... | 415 | 1 |
def A ( _lowercase , _lowercase ):
SCREAMING_SNAKE_CASE : Dict = ''''''
for word_or_phrase in separated:
if not isinstance(_lowercase , _lowercase ):
raise Exception('''join() accepts only strings to be joined''' )
... | 248 | import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__UpperCamelCase : List[Any] = logging.get_logger(__name__)
def A ( _lowercase , _lowercase ):
SCREAMING_SNAKE_CASE : Union[s... | 248 | 1 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
__A ... | 313 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCamelCase_ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ = False ):
if radian_mode:
return [magnitude * cos(lowerCamelCase__ ... | 313 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def A_ ( SCREAMING_SNAKE_CASE_ ) ->int:
if not postfix_notation:
return 0
lowercase_ = {"""+""", """-""", """*""", """/"""}
lowercase_ = []
for token in postfix_notation:
if tok... | 451 | '''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_availab... | 451 | 1 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : List[str] , __UpperCAmelCase : Optional[Any] , __Up... | 718 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class __magic_name__ ( lowerCAmelCase ):
"""... | 111 |
'''simple docstring'''
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import To... | 111 | 1 |
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=lowerCamelCase__ ):
lowerCAmelCase__ = ["""note_seq"""]
def __init__( self , *lowercase_ , **lowercase_) -> Any:
requires_backends(self , ... | 716 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
UpperCAmelCase__ : int = {
"configuration_trocr": ["TROCR_PRETRAINED_CONFIG_AR... | 676 | 0 |
from jiwer import compute_measures
import datasets
A : Dict = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved evaluation measures for connecte... | 287 |
from ...processing_utils import ProcessorMixin
class a_ ( _a ):
a : Optional[int] = '''SpeechT5FeatureExtractor'''
a : List[Any] = '''SpeechT5Tokenizer'''
def __init__( self , __UpperCamelCase , __UpperCamelCase ):
super().__init__(__Uppe... | 287 | 1 |
"""simple docstring"""
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
SCREAMING_SNAKE_CASE_ : Optional[int] = {
# 1536-bit
... | 713 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logg... | 274 | 0 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info(... | 93 | import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def _a ( lowercase__ : np.ndarray ):
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def _a ... | 85 | 0 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultist... | 427 |
'''simple docstring'''
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
_lowercase = """scheduler_config.json"""
class a_ ( UpperCAmelCase__ ):
lowercase_ : int ... | 427 | 1 |
import numpy as np
def lowerCAmelCase_ ( __a ) -> np.array:
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def lowerCAmelCase_ ( __a ) -> np.array:
"""simple docstring"""
return vector * sigmoid(1.7_0_2 * vector )
if... | 59 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowerCamelCase( lowercase__ ) -> List[Any]:
'''simple docstring'''
if not is_accelerate_available():
return method
__lowercase= vers... | 230 | 0 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCAmelCase = re.compile(R"""\b(a|an|the)\b""", re.UNICODE)
lowerCAmelCase = None
def __SCREAMING_SNAKE_CASE ( ) -> Union[str, Any]:
'''simple ... | 675 |
def __SCREAMING_SNAKE_CASE ( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
lowerCAmelCase = generate_large_matrix()
lowerCAmelCase = (
[[4, 3, 2, -1], [3, 2,... | 675 | 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 impo... | 9 |
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 ...test_modeling_co... | 395 | 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_distilbert import DistilBertTokenizer
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = ... | 82 | import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
lowerCamelCase__ = {
'''cola''': 2,... | 82 | 1 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data... | 677 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''EncodecConfig''',
],
... | 677 | 1 |
"""simple docstring"""
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 ... | 703 |
"""simple docstring"""
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def UpperCAmelCase ( ):
'''simple docstring'''
raise RuntimeError('CUDA out of me... | 133 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils impor... | 40 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 658 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def A ( _lowerCamelCase , _lowerCamelCase=False ):
'''simple docstring'''
_lowerCAmelCase : Dict = OmegaConf.load(_lowerC... | 658 | 1 |
"""simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
UpperCamelCase_ : Dict = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 115 |
'''simple docstring'''
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_we... | 452 | 0 |
import os
import sys
SCREAMING_SNAKE_CASE_ = os.path.join(os.path.dirname(__file__), """src""")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSequenceClas... | 720 |
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=lowerCAmelCase_ ):
'''simple docstring'''
__snake_case : Dict = ["sentencepiece"]
def __init__( self : int ,*lowerCamelCase__ : Any ,**lowerC... | 116 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
__a : List[str] = {"""UserAgent""": UserAgent().random}
def UpperCAmelCase ( lowercase ):
"""simple docstring"""
__lowercase ... | 534 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class a ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
UpperCamelCase_ : Tuple = 'M-CLIP'
def __init__( self : Any , lowerCamelCase__ : List[Any]=1_... | 332 | 0 |
"""simple docstring"""
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...token... | 714 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
fro... | 378 | 0 |
from collections.abc import Callable
import numpy as np
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ )-> np.ndarray:
"""simple docstring"""
... | 628 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __magic_name__ ( snake_case ):
UpperCamelCase_ :Dict = (KDPMaDiscreteScheduler,)
UpperCamelCase_ ... | 628 | 1 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
... | 701 |
def a_ ( _A , _A ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(_A ) , _A )
return number - int(_A )
if __name__ == "__main__":
print(decimal_isolate(1.5_3, 0))
print(decimal_isola... | 372 | 0 |
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 AutoTok... | 381 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin... | 381 | 1 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow_memo... | 700 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__UpperCAmelCase = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.... | 503 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A_ ( __lowerCamelCase ):
'''simple docstring'''
_UpperCame... | 84 |
def __lowerCamelCase ( _lowercase ) -> str:
return "".join(chr(ord(_lowercase ) - 32 ) if 'a' <= char <= 'z' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 282 | 0 |
import math
class lowerCamelCase_ :
def lowercase ( self , lowerCamelCase_ , lowerCamelCase_ ) -> int:
"""simple docstring"""
_UpperCamelCase = 0.0
_UpperCamelCase = 0.0
for i in range(len(__a ) ):
da +=... | 707 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_proces... | 589 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__lowercase : str ={
"""configuration_audio_spectrogram_transformer""": [
"""AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 54 |
'''simple docstring'''
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,
DistilBe... | 407 | 0 |
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_available
from ...test_confi... | 718 |
# using dfs for finding eulerian path traversal
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__=None ):
lowercase = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
lowercase , l... | 72 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : Dict = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm... | 690 |
"""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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to... | 690 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCamelCase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies # noqa: E402
# ... | 705 |
import math
def _UpperCAmelCase ( A , A ):
'''simple docstring'''
if (
not isinstance(A , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError("power_factor must be a valid floa... | 510 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {}
class UpperCAmelCase_ ( snake_case ):
UpperCamelCase ="llama"
UpperCamelCase =["past_key_va... | 76 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__lowerCamelCase : Union[str, Any] = ""
__lowerCamelCase : Dict = ""
__lowerCamelCase : Optional[int] = ""
__lowerCamelCase : Optional[A... | 416 | 0 |
"""simple docstring"""
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImagePr... | 721 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_... | 397 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import choice
def _SCREAMING_SNAKE_CASE ( __snake_case : Optional[int] ):
return choice(__snake_case )
def _SCREAMING_SNAKE_CASE ( __snake_case : list[int] , __snake_case : int )... | 107 |
"""simple docstring"""
from __future__ import annotations
class __lowercase :
'''simple docstring'''
def __init__( self , _UpperCAmelCase , _UpperCAmelCase ):
__a , __a : List[Any] =... | 52 | 0 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def A ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple do... | 433 |
from math import factorial
def A ( SCREAMING_SNAKE_CASE = 100 ):
"""simple docstring"""
return sum(map(SCREAMING_SNAKE_CASE , str(factorial(SCREAMING_SNAKE_CASE ) ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
... | 433 | 1 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def _UpperCamelCase ( UpperCamelCase__ ):
def wrapper(*UpperCamelCase__ , **UpperCamelCase__ ... | 407 |
'''simple docstring'''
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__A ='<<<<<<< This should probably be modified because it mentions: '
__A ='===... | 407 | 1 |
"""simple docstring"""
from typing import Dict
from .base import GenericTensor, Pipeline
class __lowerCAmelCase ( lowercase_ ):
def UpperCAmelCase ( self , __UpperCAmelCase=None , __UpperCAmelCase=None , __UpperCAmelCase=None , **__UpperCAmelCase ):
'''simple docstring... | 711 |
"""simple docstring"""
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 ImageProcessingSavingTestM... | 293 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_fu... | 46 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase_( ) -> None:
'''simple docstring'''
print("Making key files..." )
make_key_... | 46 | 1 |
import sys
import turtle
def UpperCamelCase ( lowerCAmelCase__ , lowerCAmelCase__ ):
'''simple docstring'''
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def UpperCamelCase ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , ... | 700 |
def UpperCamelCase ( lowerCAmelCase__ , lowerCAmelCase__ ):
'''simple docstring'''
return int((input_a, input_a).count(0 ) == 0 )
def UpperCamelCase ( ):
'''simple docstring'''
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_... | 633 | 0 |
from __future__ import annotations
import requests
_snake_case = set(
'''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc downs
... | 382 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''facebook/s2t-wav2vec2-large-en-de''': (
'''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'''
)... | 382 | 1 |
def __UpperCAmelCase ( __a : str ) -> bool:
"""simple docstring"""
_a : List[Any] = [int(__a ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(__a ) == 4 and all(0 <= int(__a ) <= 254 for octet in octets )
if __name__ == "__mai... | 578 |
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 import logging
a__ = logging.get... | 578 | 1 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('''>=''', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed.checkpoint.... | 410 |
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def _lowercase ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) -> tuple[int | None, int | None, float]... | 410 | 1 |
'''simple docstring'''
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_vis... | 708 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
A ... | 163 | 0 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCamelCase (SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
def __lt__( self : Optional[int] , __magic_name__ : int ) -... | 140 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
if... | 140 | 1 |
def A(__a: int = 100 ):
lowerCAmelCase_ = 0
lowerCAmelCase_ = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ == "__main__":
print(F'''{solution() = }''')
| 719 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class __magi... | 226 | 0 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCamelCase__ ( __lowerCamelCase : int ):
__UpperCAmelCase : Optional[Any] = prime_factors(__lowerCamelCase )
if is_square_free(__lowerCamelCase ... | 63 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-Atten... | 259 | 0 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Union[str, Any] ):
for param in module.parameters():
SCREAMING_SNAKE_CASE__ = False
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMI... | 59 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'shi-labs/nat-mini-in1k-224': 'https://hugg... | 59 | 1 |
"""simple docstring"""
from math import sqrt
def __snake_case ( SCREAMING_SNAKE_CASE: int ):
"""simple docstring"""
_lowerCAmelCase = 0
for i in range(1 , int(sqrt(SCREAMING_SNAKE_CASE ) + 1 ) ):
if n ... | 580 |
"""simple docstring"""
from __future__ import annotations
_snake_case = [True] * 1_0_0_0_0_0_1
_snake_case = 2
while i * i <= 1_0_0_0_0_0_0:
if seive[i]:
for j in range(i * i, 1_0_0_0_0_0_1, i):
_snake_case = False
i += 1
def __snake_case ( S... | 580 | 1 |
'''simple docstring'''
def snake_case ( a_ : list ) -> list:
"""simple docstring"""
if len(a_ ) <= 1:
return [tuple(a_ )]
UpperCamelCase_ : Optional[int] = []
def generate(a_ : int , a_ : list ):
... | 712 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
UpperCamelCase =["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]
def snake_case ( a_ : List[str] , a_ : Optional[Any] ) -> Union[str, Any]:
... | 543 | 0 |
import os
import time
import numpy as np
import onnxruntime as ort
lowerCamelCase__ : int = '1'
lowerCamelCase__ : Optional[int] = '0'
lowerCamelCase__ : Optional[Any] = '1'
lowerCamelCase__ : int = ort.SessionOptions()
lowerCamelC... | 31 |
'''simple docstring'''
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( __lowerCAmelCase ):
lowerCAmelCase__ : Optional[int] = (UnCLIPScheduler,)
def __a ( ... | 489 | 0 |
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:
a_ :Dict ... | 717 |
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,
ViTHybrid... | 250 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 |
"""simple docstring"""
def __snake_case ( __A : list , __A : int , __A : int = 0 , __A : int = 0 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Any = right or len(__A ) - 1
if left ... | 265 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a_ : Any = logging.get_logger(__name__)
a_ : Tuple = {
"facebook/xmod-base": "https://huggingface.c... | 710 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
a_ : Any = logging.get_logger(__name__)
a_ : Dict = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json"
),
}
... | 673 | 0 |
'''simple docstring'''
def UpperCamelCase_ ( A__ , A__ , A__ ):
def count_of_possible_combinations(A__ ) -> int:
if target < 0:
return 0
if target == 0:
return 1
return sum(count_of_possible_combinations(target - item ) for item in array )
return count_of_po... | 263 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( A__ ):
a_ = [True] * limit
a_ = False
a_ = False
a_ = True
for i in range(3 , int(limit**0.5 + 1 ) , 2 ):
a_ = i * ... | 263 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def a ( ) -> str:
__magic_name__: Any = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
_... | 213 |
"""simple docstring"""
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_tor... | 213 | 1 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCAmelCase_ ( lowerCamelCase ):
__magic_name__ , __magic_name__ : Union[str, Any] =analyze_text(lowerCamelCase )
__magic_name__ ... | 21 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase_ ( __UpperCamelCase : float , __UpperCamelCase : float , __UpperCamelCase : int ) -> float:
"""simple docstring"""
_A = ... | 292 | 0 |
def UpperCamelCase ( lowerCAmelCase_ ) -> str:
'''simple docstring'''
if number > 0:
raise ValueError('input must be a negative integer' )
_A= len(bin(lowerCAmelCase_ )[3:] )
_A= bin(abs(lowerCAmelCase_ ) - (1 << binary_numb... | 711 | import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class lowerCAmelCase ( _a ):
def __init__( self , *lowerCAmelCase__ , **lowerCAmelC... | 476 | 0 |
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
__snake_case = (
'''This metric will be removed from the library soo... | 1 |
'''simple docstring'''
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
__snake_case... | 131 | 0 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : float , __lowerCAmelCase : float , __lowerCAmelCase : float , __lowerCAmelCase : float , __lowerCAmelCase : float , ):
lowerCamelCase__ = [redshift, radiation_density, matter_density, dark... | 720 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoPro... | 9 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder, V... | 221 |
'''simple docstring'''
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( __snake_case : Optional[int] , __snake_case : Union[str, Any] , __sn... | 676 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
... | 712 |
'''simple docstring'''
from heapq import heappop, heappush
import numpy as np
def _lowercase ( UpperCamelCase__ : np.ndarray, UpperCamelCase__ : tuple[int, int], UpperCamelCase__ : tuple[int, int], UpperCamelCase__ : bool, ):
__A ,__A : Option... | 540 | 0 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowerCamelCase__ ( __lowerCamelCase : Optional[Any] , __lowerCamelCase : Optional[int]=None ):
__Upp... | 63 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xope... | 585 | 0 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {'''vocab_file'... | 498 |
"""simple docstring"""
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
def __init__( self : Any , snake_case : str , snake_case : str ):
'''simple docstring'''
A__ , A__ : List[s... | 498 | 1 |
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
UpperCam... | 37 |
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 : Any ... | 509 | 0 |
import warnings
from .generation import TFGenerationMixin
class SCREAMING_SNAKE_CASE ( snake_case ):
"""simple docstring"""
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be remove... | 62 |
def __A ( _lowercase , _lowercase , _lowercase , _lowercase ):
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
_A = mf_knapsack(i - 1 , _lowercase , _lowercase ... | 62 | 1 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def UpperCAmelCase ( A : str ):
SCREAMING_SNAKE_CASE : Any = int(number**0.5 )
return number == sq * sq
def UpperCAme... | 527 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_im... | 328 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
snake_case__ : Tuple = {
"configuration_layoutlmv3": [
"LAYOUTLMV3_PRETRAINED... | 705 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def lowercase ( __A : bytes , __A : int ) -> np.array:
'''simple docstring'''
snake_case : List[str] = f"""{sampling_rate}"""
snake_... | 315 | 0 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_... | 595 |
"""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 MaskGenerationPipeline
from t... | 595 | 1 |
'''simple docstring'''
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
... | 720 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase_ ( lowercase__ , lowercase__ , lowercase__):
lowerCamelCase__ = list(range(len(lowercase__)))
lowerCamelCase__ = [v / w for v, w in zip(lowercase__ , lowercase__)]
index.sort(key=la... | 187 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a__ = {
'''configuration_perceiver''': ['''PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Pe... | 14 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBas... | 96 | 0 |
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
@maybe_allow_in_graph
cla... | 633 |
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."
)
| 633 | 1 |
def UpperCAmelCase ( a_ ) -> list:
"""simple docstring"""
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(a_ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('doctest').testmod()
| 55 |
"""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/LI... | 673 | 0 |
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compute_metrics as com... | 62 |
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
__A = logging.getLogger(__name__)
if is_torch_tpu_available(check_device=False):
imp... | 62 | 1 |
'''simple docstring'''
import cmath
import math
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : int = math.radians(lowerCamelCase__ )
A_ : List[str] = math.radians(lowerCamelCase_... | 667 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as... | 667 | 1 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = R'\n Args:\n input_ids (`torch.LongTensor` of shape `(... | 709 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
UpperCamelCase_ = transforms.Compo... | 142 | 0 |
def lowerCamelCase( a__ ,a__ ,a__):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(a__))
def lowerCamelCase( a__ ,a__ ,a__ ,a__):
# Base Case
if index == len(a__):
return True
# Recursive ... | 691 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
snake_case_ : Dict = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
snake_case_ : Union[str, Any] = ... | 691 | 1 |
import math
def lowerCamelCase__ ( __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(__lowerCAmelCase )
def lowerCamelCase__... | 704 |
import math
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase=0 ) -> Tuple: # a graph with Node 0,1,...,N-1
lowerCAmelCase_ = n
lowerCAmelCase_ = [
[math.inf for j in range(0 , _UpperCamelCase )] for i ... | 279 | 0 |
_lowerCAmelCase: Union[str, Any] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCAmelCase: int = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCAmelCase: Any = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
... | 20 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('''hub/hopper-medium-v2/unet/hor32''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/unet/hor128''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/value_function''', exist_ok=True)
def A ( __UpperCamelCase ... | 9 | 0 |
'''simple docstring'''
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configurat... | 708 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, ... | 599 | 0 |
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