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 |
|---|---|---|---|---|
from __future__ import annotations
def a ( snake_case__: Optional[int] , snake_case__: Optional[int] , snake_case__: Any , snake_case__: Optional[int] ): # noqa: E741
'''simple docstring'''
while r - l > 1:
lowercase_ = (l + r) // 2
if v[m] >=... | 97 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def a ( snake_case__: Any ... | 97 | 1 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : int ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 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 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _snake_case ( lowerCAmel... | 216 | import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__lowerCamelCase : str = get_logger(__name__)
class a__ ( enum.Enum ):
A = 'all_checks'
A = 'basic_checks'
A ... | 216 | 1 |
def _SCREAMING_SNAKE_CASE ( lowercase : Optional[Any] ):
'''simple docstring'''
lowerCamelCase_ = int(lowercase )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowercase )
lowerCamelCase_ , lowerCamelCase_ =... | 703 |
lowerCamelCase : Dict = "Alexander Joslin"
import operator as op
from .stack import Stack
def _SCREAMING_SNAKE_CASE ( lowercase : str ):
'''simple docstring'''
lowerCamelCase_ = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
... | 651 | 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... | 298 |
import argparse
import copy
def __magic_name__ ( __lowerCAmelCase : List[str] ) -> Optional[Any]:
__lowerCamelCase = {}
with open(__lowerCAmelCase ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
__lowerCamelC... | 298 | 1 |
'''simple docstring'''
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 lowerCamelCase ( unittes... | 704 | '''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
lowercase__ : str = datasets.logging.get_logger(__name__)
lowercase__ : Dict = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and ... | 43 | 0 |
_a : List[Any] = [
(1_000, 'M'),
(900, 'CM'),
(500, 'D'),
(400, 'CD'),
(100, 'C'),
(90, 'XC'),
(50, 'L'),
(40, 'XL'),
(10, 'X'),
(9, 'IX'),
(5, 'V'),
(4, 'IV'),
(1, 'I'),
]
def a_ ( __magic_name__ ) -> in... | 598 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggin... | 598 | 1 |
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_... | 284 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_avai... | 284 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
a : List[str] = r"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the mod... | 63 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowercase : Optional[Any] = """http://www.mocksite.com/... | 336 | 0 |
'''simple docstring'''
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __UpperCAmelCase ( A : Optional[Any] ) -> List[str]:
UpperCAmelCase_ : Dict = {}
UpperCAmelCase_ : List[Any] = job['''sta... | 708 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def __UpperCAmelCase ( A : np.ndarray ) -> np.ndarray:
UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ : int = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
re... | 216 | 0 |
'''simple docstring'''
import re
def _UpperCAmelCase ( __A : str ):
if len(re.findall('''[ATCG]''' , __lowerCamelCase ) ) != len(__lowerCamelCase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' ... | 466 |
'''simple docstring'''
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class a_ ( snake_case_ ):
'''si... | 314 | 0 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
__UpperCAmelCase = input("""Enter image url: """).strip()
print(F'Downloading image from {url} ...')
__UpperCAmelCase = BeautifulSoup(requests.get(url).content, """html.parser"""... | 218 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoM... | 218 | 1 |
from typing import Any
class snake_case__ :
def __init__( self : Optional[int] , _lowerCamelCase : Any ):
snake_case__ : int = data
snake_case__ : Dict = None
def __repr__( self : Tuple ):
re... | 170 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase : int = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
'tokenization_biogpt': ['BioGptToke... | 170 | 1 |
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
__A : Union[str, Any] = parse(importlib.metadata.version("""torch"""))
def lowerCamelCase_ ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ... | 450 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
__A : Tuple = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
from .safilesystem import S... | 450 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"edbeeching/decision-transformer-gym-hopper-medium": (
"https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/c... | 109 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithP... | 109 | 1 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
_A = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": opera... | 710 |
"""simple docstring"""
from math import isqrt
def lowercase_ ( __UpperCAmelCase ) -> bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(__UpperCAmelCase ) + 1 ) )
def lowercase_ ( __UpperCAmelCase = 10**6 ) -> int:
lowerCAmelCase__ ... | 507 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
# TODO: upload to AWS
lowerCAmelCase__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retrib... | 645 |
"""simple docstring"""
from string import ascii_uppercase
lowerCAmelCase__ = {str(ord(c) - 55): c for c in ascii_uppercase}
def a__ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
if isinstance(SCREAMING... | 645 | 1 |
"""simple docstring"""
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("""3.8"""):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
... | 708 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : List[str] = {
"""configuration_autoformer""": [
"""AUTOFORMER_PRETRAINED_CONFI... | 533 | 0 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig... | 672 |
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_neuroncore,
)
from... | 509 | 0 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : List[Any] = {
'''snap-research/efficientformer-l1-300''': (
'''https://huggingface.co/... | 721 |
"""simple docstring"""
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def _lowerCAmelCase ( lowerCamelCase__ : Sequence[float], lowerCamelCase__ : int, l... | 295 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFM... | 620 |
'''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_torch_available():
impor... | 689 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A = {
'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
'feature_extraction_mctct': ['MCTCTFeatureExtractor'],
... | 704 | '''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def _UpperCamelCase ( SCREAMING_SNAKE_CASE_ ):
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise TypeError('Undefined for non-integers' ... | 438 | 0 |
'''simple docstring'''
from __future__ import annotations
_a : Dict = list[tuple[int, int]]
_a : str = [
[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],
[1, 0, 1, 0, 0,... | 56 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
__SCREAMING_SNAKE_CASE = TypeVar("""T""")
class __snake_case ( Generic[T] ):
"""simple docstring"""
def __init__( self :Tuple ... | 388 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class UpperCAmelCase ( snake_case_):
"""simple docstring"""
def UpperCamelCase__ ( self : Union[str, Any] ) -> Optional[... | 701 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_to... | 271 | 0 |
'''simple docstring'''
_a : Union[str, Any] = "\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git... | 56 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import... | 430 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_A = logging.get_logger(__name__)
_A = '''▁'''
_A = {'''v... | 325 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from... | 325 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : List[str] = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig",
... | 242 |
'''simple docstring'''
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_... | 679 | 0 |
'''simple docstring'''
import baseaa
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> bytes:
return baseaa.baaencode(string.encode("""utf-8""" ) )
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : bytes ) -> s... | 506 |
'''simple docstring'''
A__: Dict = {
'''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... | 506 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class UpperCamelCase (unittest.TestCase ... | 264 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCamelCase :
def __init__( self :Any , __magic_name__ :list[tuple[float, float]] ) ->str:
lowercase : List[Any] = list_of_points
... | 264 | 1 |
class UpperCamelCase :
def __init__( self , UpperCAmelCase__ , UpperCAmelCase__ ):
A__ = name
A__ = val
def __str__( self ):
return F"""{self.__class__.__name__}({self.name}, {self.val})"""
def __lt__( self , UpperCAmelCase__ ):
retur... | 232 |
def UpperCamelCase ( _A : int = 50 )-> int:
"""simple docstring"""
A__ = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_sta... | 232 | 1 |
def __UpperCAmelCase( ):
for n in range(1 , 1_00_00_00 ):
yield n * (n + 1) // 2
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : Any = 1
_lowerCamelCase : Dict = 2
while i * i <= n:
_lowerCamelCase : List[... | 114 |
"""simple docstring"""
from graphs.minimum_spanning_tree_kruskal import kruskal
def __snake_case ( ):
"""simple docstring"""
_lowerCAmelCase = 9
_lowerCAmelCase = [
[0, 1, 4],
[0, 7, 8],
[... | 580 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase_ ( _lowercase , _lowercase , _lowercase ) -> ... | 357 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowercase : Any = logging.get_logger(__name__)
__lowercase... | 357 | 1 |
def SCREAMING_SNAKE_CASE ( snake_case = 1_000 ) -> int:
__lowercase , __lowercase = 1, 1
__lowercase = []
for i in range(1 , n + 1 ):
__lowercase = prev_numerator + 2 * prev_denominator
__lowercase = pr... | 375 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
SCREAMING_SNAKE_CASE_ : str = {
'''... | 375 | 1 |
'''simple docstring'''
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_se... | 721 |
'''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_ut... | 223 | 0 |
from __future__ import annotations
import time
import numpy as np
snake_case : Union[str, Any] = [8, 5, 9, 7]
snake_case : Optional[int] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
snake_case : Union[str, Any] ... | 605 |
from __future__ import annotations
from typing import Any
def SCREAMING_SNAKE_CASE ( UpperCAmelCase__ ):
"""simple docstring"""
if not postfix_notation:
return 0
_SCREAMING_SNAKE_CASE = {'+', '-', '*', '/'}
_SCREAMING_SNAKE_CASE = []
f... | 605 | 1 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase ( snake_case__ ):
'''simple docstring'''
A = (KDPMa... | 304 | """simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
... | 304 | 1 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase ( __UpperCAmelCase ):
@require_torch
def lowerCamelCase_ ( self :... | 386 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''... | 674 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"microsoft/swinv2-tiny-patch4-window8-256": (
"https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
)... | 202 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 202 | 1 |
from math import pi, sqrt, tan
def A__ ( snake_case_ : float ):
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''' )
return 6 * side_length**2
def A__ ( snake_case_ : float , snake_case_ : float , s... | 64 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Dict = {
"""ut/deta""": """htt... | 116 | 0 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers... | 703 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTe... | 519 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : Dict = {
'''microso... | 549 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class a ( unittest.TestCa... | 549 | 1 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Op... | 714 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision... | 485 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowercase_ ,lowercase_ ) -> list[int]:
"""simple docstring"""
_UpperCamelCase : List[Any] = 0
_UpperCamelCase : Optional[int] = len(__UpperCamelCas... | 624 |
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 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import... | 62 |
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 SCREAMING_SNAKE_CASE ( snake_case , unittest.TestCase ... | 62 | 1 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_avai... | 438 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class lowerCAmelCase__ :
def __init__( self : Any , snake_case__ : Any ):
'''simple docstring'''
UpperCAmelCase__ : Any = ... | 438 | 1 |
def UpperCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase ) -> Tuple:
__lowercase : str = [1]
for i in range(2 , __lowerCAmelCase ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k out of bounds"
__lowercase : Any ... | 284 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
... | 284 | 1 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
blenderbot,
blenderbot_... | 216 | from itertools import product
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = sides_number
SCREAMING_SNAKE_CASE_ : List[str] = max_face_number * dice_number
SCREAMI... | 216 | 1 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __A ( _UpperCamelCase ):
"""simple docstring"""
def A__ ( self , __snake_case):
with open(__a , encoding='utf-8') as input_file:
_UpperCamelCase :... | 707 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase__ = {
"""configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CanineConfig"""],
"""tokenization_canine""": ["""CanineToke... | 648 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : int = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
"""feature_extraction_mc... | 452 |
'''simple docstring'''
from torch import nn
def snake_case_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise Value... | 672 | 0 |
"""simple docstring"""
def A__ ( UpperCamelCase__ ):
'''simple docstring'''
_SCREAMING_SNAKE_CASE = len(UpperCamelCase__ )
for i in range(length - 1 ):
_SCREAMING_SNAKE_CASE = i
for k in range(i + 1 , UpperCamelCa... | 168 |
"""simple docstring"""
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def A__ ( UpperCamelCase__ = "laptop" ):
'''simple docstring'''
_SCREAMING_SNAKE_CASE = F'''https://www.amazon.in/l... | 168 | 1 |
import math
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : int ):
UpperCamelCase_ : Tuple = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(_SCREAMING_SNAKE_CASE )
def lowerCAmelCase_ ( _SCREAMING_SNAKE_... | 635 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelera... | 273 | 0 |
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub... | 703 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, ge... | 303 | 0 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def a_ ( __UpperCAmelCase ) -> datetime:
"""simple docstring"""
snake_case: List[str] =year % 19
snake_case: int =year % 4
snake_... | 350 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a = {
'configuration... | 350 | 1 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __magic_name__ ( unittest.TestCase ):... | 712 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
i... | 331 | 0 |
"""simple docstring"""
from itertools import product
def __magic_name__ ( UpperCamelCase : int , UpperCamelCase : int ) -> list[int]:
a__ = sides_number
a__ = max_face_number * dice_number
a__ = [0] * (max_total + 1)
a__ = 1
a__ = range(... | 273 |
"""simple docstring"""
import math
class lowercase:
def lowercase__ ( self , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
a__ = 0.0
a__ = 0.0
for i in range(len(__SCREAMING_SNAK... | 273 | 1 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __magic_name__ ( unittest.TestCase):
def UpperCAmelCase__ ( self : s... | 106 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __magic_name__ ( __lowerCAmelCase):
A:... | 106 | 1 |
"""simple docstring"""
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _snake_case :
'''simple docstring'''
def __init__( self : List[Any] , snake_case : int , snake_case : int , snake_case : int ):
if dst_wi... | 608 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase_ : int = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
"""tokenization_tran... | 461 | 0 |
from __future__ import annotations
from cmath import sqrt
def lowerCamelCase__ ( __lowerCAmelCase : int , __lowerCAmelCase : int , __lowerCAmelCase : int ):
"""simple docstring"""
if a == 0:
raise ValueError("Coefficient ... | 279 |
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 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from .... | 4 | '''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
... | 274 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A : Optional[Any] ={'''configuration_xlnet''': ['''XLNE... | 4 |
'''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 __UpperCamelCase ( _lowercase ... | 4 | 1 |
from __future__ import annotations
def __UpperCAmelCase ( __a : list[int] ,__a : int ) -> int:
"""simple docstring"""
if len(__a ) < k or k < 0:
raise ValueError('''Invalid Input''' )
_a : Any = sum(array[:k] )... | 14 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from numpy import array
def a ( __a ) -> list[list[float]]:
'''simple docstring'''
UpperCamelCase__ :int = Decimal
# Check if the provided matrix has 2 rows and 2 columns
... | 189 | 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... | 715 |
from math import ceil, sqrt
def _a ( SCREAMING_SNAKE_CASE_ : int = 1_00_00_00 ):
__lowerCAmelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
__lowerCAmelCase = max(ceil(sqrt(outer_width**2 ... | 552 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> Optional[int]:
'''simple docstring'''
if p < 2:
raise ValueError("p should not be less than 2!" )
elif p == 2:
return True
A__ = 4
A__ = (1 << p) - 1
for _ ... | 514 |
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def _UpperCAmelCase (UpperCamelCase__ : U... | 503 | 0 |
import json
from typing import TYPE_CHECKING, 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_blenderbot import Ble... | 706 |
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
logging,... | 429 | 0 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def lowerCamelCase__ ( _lowercase ):
'''simple docstring'''
for param in module.parameters():
UpperCAmelCase_ : str = False
def lowerCamelCase__ ( ):
'''simple docstring'''
... | 30 |
"""simple docstring"""
from torch import nn
class lowerCAmelCase__ ( nn.Module ):
'''simple docstring'''
def __init__( self : Union[str, Any] , lowercase_ : str , lowercase_ : str):
'''simple docstring'''
super().__ini... | 512 | 0 |
'''simple docstring'''
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __magic_name__ ( UpperCAmelCase__):
def SCREAMING_SNAKE_CASE_ ( self : Optional[int] , lowercase_ : str ):
... | 709 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer,... | 30 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformer... | 212 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case_ : Optional[Any] = {
'configuration_blende... | 212 | 1 |
"""simple docstring"""
from __future__ import annotations
def __UpperCAmelCase ( _snake_case : float, _snake_case : float, _snake_case : float ):
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("One and only one argument must be 0" )
if ... | 227 | """simple docstring"""
import argparse
import datetime
def __UpperCAmelCase ( _snake_case : str ):
_lowercase = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturday",
}
... | 227 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , _lowerCamelCase : int ) -> None:
__magic_name__ = val... | 664 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Union[str, Any] ={'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
try:
... | 664 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=__A ):
"""simple docstring"""
lowerCamelCase = ['''note_seq''']
def __init__( self , *_lowerCamelCase , **_lowerCamelCase ... | 385 |
'''simple docstring'''
import numpy as np
import qiskit
def UpperCAmelCase ( a_ = 8 , a_ = None ) -> str:
"""simple docstring"""
A_ : List[Any] = np.random.default_rng(seed=a_ )
# Roughly 25% of the qubits will contribute to ... | 385 | 1 |
import unittest
from transformers import DonutProcessor
a_ : List[Any] = 'naver-clova-ix/donut-base'
class lowerCamelCase__ ( unittest.TestCase):
"""simple docstring"""
def _a (self ):
'''simple docstring'''
... | 623 |
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowercase( UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ ):
"""... | 623 | 1 |
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
lowercase = logging.getLogger()
def UpperCAmelCase_ ... | 709 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase = logging.get_logger(__name__)
lowercase = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
... | 41 | 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
lowercase : Dict = logging.get_logger(__name__)
lowercase : Tuple = {
"s... | 327 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversation... | 327 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenization_ctrl""": ["""CTRLTokenizer"""],
}
try:
... | 531 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
UpperCAmelCase = {"""UserAgent""": UserAgent().random}
def __lowerCAmelCase (SCREAMING_SNAKE_CASE )-> dict:
"""simple docstring"""
snake_ca... | 531 | 1 |
'''simple docstring'''
import numpy as np
lowerCAmelCase__ : List[str] = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", ""... | 347 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 347 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCAmelCase = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:
if not is_torch_available():
raise OptionalDependen... | 589 |
def _lowercase ( a__ : int , a__ : int ) -> float:
"""simple docstring"""
return base * power(a__ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print("""Raise base to the power of exponent using recursion...""")
__lowerCAmelCase = int(i... | 589 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__magic_name__ = {'''configuration_encoder_decoder''': ['''EncoderDecoderConfig''']}
try:
if not is_torch_available():
... | 276 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''vocab_file''': '''vocab.json''',
'''merges_file''': '''merges.t... | 276 | 1 |
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 (
AutoProcessor,
... | 718 | import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import... | 234 | 0 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedul... | 2 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _A ( __snake_case :int , __snake_case :int , __snake_case :int , __snake_case :int , __snake_case :int , __snake_case :int ) -> np.ndarray:
"""simple doc... | 693 | 0 |
"""simple docstring"""
def _A ( __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_tab... | 714 |
"""simple docstring"""
class SCREAMING_SNAKE_CASE__ : # Public class to implement a graph
def __init__( self : Union[str, Any] , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : list[list[bool]] ):
lower... | 258 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def lowercase (SCREAMING_SNAKE_CASE_ : Any ) -> Op... | 247 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from... | 247 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 1000 ) -> int:
'''simple docstring'''
snake_case_ ,snake_case_ = 1, 1
snake_case_ = 2
while True:
snake_case_ = 0
snake_case_ = fa + fa
sn... | 593 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 1000 ) -> int:
'''simple docstring'''
snake_case_ ,snake_case_ = 1, 1
snake_case_ = 2
while True:
snake_case_ = 0
snake_case_ = fa + fa
sn... | 593 | 1 |
"""simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
fr... | 110 |
"""simple docstring"""
import math
import os
import sys
def _lowercase ( __lowerCAmelCase ) -> str:
SCREAMING_SNAKE_CASE__ : Union[str, Any] = """"""
try:
with open(__lowerCAmelCase , """rb""" ) as binary_file:
SCREAMING_SNA... | 680 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A , __A):
"""simple docstring"""
print(F'''Vertex\tShortest Distance from vertex {src}''')
for i, d in enumerate(lowercase__):
print(F'''{i}\t\t{d}''')
def lowerCAmelCase (__A... | 719 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 352 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
class A__ :
'''simple docstring'''
def __init__( self: Union[str, Any] , _SCREAMING_SNAKE_CASE: int) -> None:
"""simple docstring"""
__lowerCAmelCase : ... | 293 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepie... | 293 | 1 |
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from ... | 82 | import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def lowerCAmelCase__ ( a__ , a__ , a__ ) ->int:
'''simple docstring'''
_UpperCamelCase ... | 82 | 1 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availa... | 199 |
__a = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
def lowerCamelCase__ ( _lowercase ):
'''simple docstring'''
if not isinstance(_lowercase , _lowercase ):
UpperCAmelCase_ : Union[str, Any] = f'''a bytes-like object is require... | 30 | 0 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowerCAmelCase( a__ : str ):
'''simple docstring'''
lowerCamelCase__ = [
"encoder.vers... | 426 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_... | 426 | 1 |
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 A_ ( unittest.TestCase ):
'''simple docstring'''
def ... | 84 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE mode... | 7 | 0 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( _a):
'''simple docstring'''
__UpperCamelCase : Dict = (DDPMScheduler,)
def _lowercase ( self , **__SCREA... | 710 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 643 | 0 |
"""simple docstring"""
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... | 160 |
def _SCREAMING_SNAKE_CASE ( snake_case ) -> int:
if not numbers:
return 0
if not isinstance(snake_case , (list, tuple) ) or not all(
isinstance(snake_case , snake_case ) for number in numbers ):
raise Val... | 518 | 0 |
"""simple docstring"""
from math import pow, sqrt
def UpperCamelCase ( *SCREAMING_SNAKE_CASE_ ) ->bool:
_lowerCamelCase : List[Any] = len(SCREAMING_SNAKE_CASE_ ) > 0 and all(value > 0.0 for value in values )
return result
def UpperCamelCase ( SCREAMING_S... | 558 | """simple docstring"""
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import ... | 558 | 1 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
lowerCAmelCase_ = '... | 60 |
def lowerCAmelCase_ ( __UpperCAmelCase: str ) -> str:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 253 | 0 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_lowerCamelCase : Any = logging.get_logger(__name__)
class snake_case__ ( _UpperCamelCase ):
'''simple docstring'''
def __init__( self ... | 707 |
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _lowerCAmelCase ( __magic_name__ :str , __magic_name__ :str , __magic_name__ :Optional[str] = None ):
if version.parse(hfh.__version__ ... | 407 | 0 |
UpperCAmelCase : dict[tuple[int, int, int], int] = {}
def _A ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
if late == 3 or absent == 2:
return 0
# if we have no days left... | 563 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
__lowercase : Optional[Any] = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''albert-large-v1''':... | 36 | 0 |
'''simple docstring'''
def snake_case_ ( __snake_case : Union[str, Any]) -> Optional[int]:
lowerCAmelCase_ = 1
lowerCAmelCase_ = 2
while i * i <= n:
lowerCAmelCase_ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_di... | 717 | '''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from de... | 606 | 0 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a = ... | 350 |
'''simple docstring'''
from __future__ import annotations
def a_ ( __UpperCAmelCase ) -> list[int]:
"""simple docstring"""
snake_case: Tuple =[True] * limit
snake_case: Optional[int] =False
snake_case: U... | 350 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCamelCase__ : list[list] ) -> list[list]:
_SCREAMING_SNAKE_CASE : Optional[Any] = current_set.copy()
for row_index, row in enumerate(lowerCamelCase__ ):
_SCREAMING_SNAKE_CASE : Any = row[0]
... | 704 |
"""simple docstring"""
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _lowerCAmelCase ( lowerCamelCase__ : Any, lowerCamelCase__ : Optional[Any], lowerCamelCase__ : List... | 295 | 0 |
"""simple docstring"""
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)... | 96 |
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 UpperCAmelCase__ ( A_ ):
'''simple docstring'''
... | 322 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_A = {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvai... | 279 |
from string import ascii_lowercase, ascii_uppercase
def lowerCamelCase__ ( __lowerCAmelCase : str ):
"""simple docstring"""
if not sentence:
return ""
lowerCAmelCase_ = dict(zip(__lowerCAmelCase , __lowerCAmelCase ) )
return... | 279 | 1 |
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