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"""
def _UpperCamelCase ( UpperCamelCase ) -> bool:
"""simple docstring"""
if not isinstance(UpperCamelCase , UpperCamelCase ):
raise ValueError("check_bouncy() accepts only integer arguments" )
__UpperCAmelCase : Optional... | 77 |
"""simple docstring"""
from typing import Any
class a__ :
def __init__( self : List[str] , UpperCamelCase_ : Any):
"""simple docstring"""
__UpperCAmelCase : str = data
__UpperCAmelCase : Optional[Any] = None
... | 77 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : Any = {
"""configuration_blenderbot_small""... | 187 |
'''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 | 1 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset... | 409 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common im... | 79 | 0 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urllib.p... | 626 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
@require_tf... | 626 | 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... | 473 | """simple docstring"""
from __future__ import annotations
def lowerCAmelCase_ (_SCREAMING_SNAKE_CASE :tuple[int, int] , _SCREAMING_SNAKE_CASE :int ) -> list[tuple[int, int]]:
a_ , a_ : Optional[int] = position
a_ : Optional[Any] = [
... | 473 | 1 |
'''simple docstring'''
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, t... | 703 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torch.uti... | 92 | 0 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
_UpperCAmelCase : Optional[int] = logging.get... | 107 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 626 | 0 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ... | 207 |
def SCREAMING_SNAKE_CASE( __UpperCamelCase ) -> float:
a__ : Optional[Any] = 0
while len(__UpperCamelCase ) > 1:
a__ : str = 0
# Consider two files with minimum cost to be merged
for _ in range(2 ):
a__ : List[str] = file... | 207 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squee... | 581 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowercase__ = {
"configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"],
}
try:
... | 581 | 1 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .log... | 496 | '''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowercase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase_ : Tuple = ['''image_processor''', '''tokenizer''']
... | 496 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ = {
'configuration_pix2struct': [
'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Pix2StructConfig',
'Pix2Str... | 685 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'uclanlp/visualbert-vqa': 'https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json',
'uclanlp/visualbert-vqa-pre': 'https://h... | 685 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
Aut... | 714 |
"""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 i... | 363 | 0 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase ) -> bool:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("check_bouncy() accepts only integer arguments" )
_lowerCamelCase : Any = ... | 46 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 46 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : str = logging.get_logger(__name__)
__lowerCAmelCase : Dict = {
"facebook/xl... | 284 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
Compute... | 284 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision_a... | 611 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
... | 614 | 0 |
'''simple docstring'''
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 ImageProcessingSavingTestM... | 709 |
'''simple docstring'''
def __snake_case ( _UpperCAmelCase : Optional[int]):
UpperCamelCase = []
UpperCamelCase = []
UpperCamelCase = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
'''%''': 2,
'''+''': 1,
'''-''': 1,
} ... | 350 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing... | 690 |
"""simple docstring"""
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,... | 690 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE = {'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNo... | 710 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 0 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase ) -> bool:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("check_bouncy() accepts only integer arguments" )
_lowerCamelCase : Any = ... | 46 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer i... | 675 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A__: Optional[int] = {
'''configuration_tapas''': ['''TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TapasConfig'''],
... | 719 |
from __future__ import annotations
def lowerCAmelCase_ ( A_ ,A_ ,A_):
if (voltage, current, resistance).count(0) != 1:
raise ValueError("One and only one argument must be 0")
if resistance < 0:
raise ValueError("Resistance cannot be negative")
... | 221 | 0 |
'''simple docstring'''
from __future__ import annotations
def A (__lowerCamelCase :str ):
return [ord(__lowerCamelCase ) - 96 for elem in plain]
def A (__lowerCamelCase :list[int] ):
return "".join(chr(elem + 96 ) for elem in encoded )
def A ():
_lowerCAmelCase ... | 5 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
_lowercase = """https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
_lowercase ... | 5 | 1 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_... | 291 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"""kakaobrain/a... | 291 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A = 1_0_0_0 ) -> int:
"""simple docstring"""
_UpperCAmelCase ,_UpperCAmelCase = 1, 1
_UpperCAmelCase = 2
while True:
_UpperCAmelCase = 0
_UpperCAmelCase = fa + fa
_UpperCAmelC... | 555 |
"""simple docstring"""
def _UpperCamelCase ( _A = 1_0_0_0 ) -> int:
"""simple docstring"""
_UpperCAmelCase ,_UpperCAmelCase = 1, 1
_UpperCAmelCase = 2
while True:
_UpperCAmelCase = 0
_UpperCAmelCase = fa + fa
_UpperCAmelC... | 555 | 1 |
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
_lowerCamelCase : List[Any] = argparse.ArgumentParser()
parser.add_argument(
'''--checkpoint_path''', default=None, ... | 516 |
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
_lowerCamelCase : List[Any] = argparse.ArgumentParser()
parser.add_argument(
'''--checkpoint_path''', default=None, ... | 516 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampl... | 428 |
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 transformers.testing_utils... | 428 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_tor... | 717 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
__lowerCamelCase = namedtupl... | 213 | 0 |
def lowerCamelCase_ ( _UpperCamelCase ) -> int:
"""simple docstring"""
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += ... | 60 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : Tuple = {
'huggingface/time-series-transformer-tourism-monthly': (
... | 212 | 0 |
from collections import deque
from .hash_table import HashTable
class UpperCamelCase__( lowerCAmelCase__ ):
"""simple docstring"""
def __init__( self : Optional[int] , *snake_case__ : Optional[int] , **snake_case__ : str ):
"""simple docstring"""
super().__... | 689 |
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__a = logging.get_logger(__name__)
__a ... | 689 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencep... | 342 |
'''simple docstring'''
_lowercase = {
"joule": 1.0,
"kilojoule": 1_000,
"megajoule": 1_000_000,
"gigajoule": 1_000_000_000,
"wattsecond": 1.0,
"watthour": 3_600,
"kilowatthour": 3_600_000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,... | 342 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowerCAmelCase : int ={
'configuration_ernie': ['ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieConfig', 'ErnieOnnxConfig'],
}
try:
... | 693 |
import torch
from diffusers import DiffusionPipeline
class _a ( snake_case_ ):
def __init__( self , lowercase_ , lowercase_ ) -> int:
super().__init__()
self.register_modules(unet=lowercase_ , scheduler=lowercase... | 693 | 1 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( __lowerCamelCase ):
"""simple docstring"""
__UpperCAmelCase : int = ... | 250 |
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 lowerCAmelCase__ ( unittest... | 250 | 1 |
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
lowercase : List[Any] = {
# 1536-bit
5: {
"""prime""": int(
... | 584 | from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class a__ ( __SCREAMING_SNAKE_CASE ):
_A = DistilBertTo... | 584 | 1 |
"""simple docstring"""
from math import sqrt
def A_ ( snake_case__ = 1_00_00_00 ) -> int:
_UpperCamelCase :int = 0
_UpperCamelCase :int = 0
_UpperCamelCase :int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in... | 355 |
"""simple docstring"""
def A_ ( snake_case__ , snake_case__ = " " ) -> list:
_UpperCamelCase :List[str] = []
_UpperCamelCase :int = 0
for index, char in enumerate(snake_case__ ):
if char == separator:
split_words.append(string[last_i... | 355 | 1 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'''kwargs, expected''' , [
({'''num_shards''': 0, '''max_num_jobs''': 1}, []),
({'''num_shards''': 10, ''... | 417 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase : Optional[Any] = {
'''configuration_convnext''': ['''CONVNEXT... | 417 | 1 |
'''simple docstring'''
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _U... | 330 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class _UpperCAmelCase ( snake_case_ ):
"""simple docstring"""
def __init__( self : int , __UpperCAmelCase : Optional[... | 330 | 1 |
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load_metric
from .utils ... | 717 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(check_device=Fals... | 99 | 0 |
'''simple docstring'''
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 OptionalDependencyNotAvail... | 44 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transform... | 44 | 1 |
from math import ceil, sqrt
def __lowerCAmelCase ( UpperCamelCase = 1000000 ) -> int:
lowerCAmelCase__ : Dict = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
lowerCAmelCase__ : Optional[int] = max(ceil(s... | 700 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __lowerCAmelCase ( UpperCamelCase ) -> str:
for param in module.parameters():
lowerCAmelCase__ : int = False
def __lowerCAmelCase ( ) -> Optional[Any]:
lowerCAmelCase__ ... | 470 | 0 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoToken... | 396 | '''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_par... | 396 | 1 |
import requests
from bsa import BeautifulSoup
def lowerCamelCase ( UpperCamelCase : str = "https://www.worldometers.info/coronavirus" ) -> dict:
_lowerCamelCase = BeautifulSoup(requests.get(UpperCamelCase ).text , 'html.parser' )
_lowerCamelCase... | 702 | from itertools import product
def lowerCamelCase ( UpperCamelCase : int , UpperCamelCase : int ) -> list[int]:
_lowerCamelCase = sides_number
_lowerCamelCase = max_face_number * dice_number
_lowerCamelCase = [0] * ... | 234 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
# See all Cvt models at https://huggingface... | 204 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
... | 204 | 1 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.ut... | 712 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTes... | 268 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_... | 465 |
'''simple docstring'''
def lowerCamelCase ( __lowerCamelCase : int = 1000 ) ->int:
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 314 | 0 |
'''simple docstring'''
# Imports
import numpy as np
class __snake_case :
def __init__( self, A=None, A=None, A=None, A=None, A=None ):
"""simple docstring"""
self.set_matricies(red=A, green=A, blue=A, red_edge=A, nir=A ... | 449 |
'''simple docstring'''
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, Swin... | 449 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( __lowerCAmelCase , __lowerCAmelCase ) -> List[str]:
'''simple docstring'''
assert x is not None
assert y is not None
lowerCamelCase__ =len(__lowerCAmelCase )
lowerCamelCase__ =len(__lowerCAmelCase... | 530 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a =logging.get_logger(__name__)
a ={
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
class __UpperCAmelCase ( __lowe... | 530 | 1 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__lowerCAmelCase : Any =""
__lowerCAmelCase : Optional[Any] =""
__lowerCAmelCase : Tuple =""
__lowerCAmelCase : List[Any] =1 # (0 is vertical, 1 is horizonta... | 704 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@... | 260 | 0 |
'''simple docstring'''
import argparse
import os
from accelerate.utils import ComputeEnvironment
from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file # noqa: F401
from .config_utils import _ask_field, _ask_option... | 143 | """simple docstring"""
from __future__ import annotations
def _A( lowerCAmelCase ):
if len(lowerCAmelCase ) == 0:
return []
A__ , A__ : Dict = min(lowerCAmelCase ), max(lowerCAmelCase )
A__ : List[Any] = int(... | 363 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
'https://huggingface.co/mi... | 703 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
__lowercase : List[Any] = len(__UpperCamelCase )
__lowercase : Optional[Any] = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value... | 523 | 0 |
def UpperCamelCase_( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
_UpperCamelCase = generate_large_matrix()
_UpperCamelCase = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
... | 146 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common im... | 146 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowerCAmelCase_ : List[Any] = {'tokenization_byt5': ['ByT5Tokenizer']}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
lowerCAmelCase_ : An... | 521 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ : List[Any] = {
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip... | 521 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase = False ) -> Optional[int]:
if not arr:
return 0
SCREAMING_SNAKE_CASE__ : List[str] = 0 if allow_empty_subarrays else float("""-inf... | 680 |
"""simple docstring"""
def lowercase_ ( _snake_case ):
if not head:
return True
# split the list to two parts
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ : Dict = head.next, head
while fast and fast.next:
SCREAMING_SNAKE_CASE__ : ... | 223 | 0 |
'''simple docstring'''
from __future__ import annotations
_A : List[str] ='''Muhammad Umer Farooq'''
_A : List[Any] ='''MIT'''
_A : Union[str, Any] ='''1.0.0'''
_A : str ='''Muhammad Umer Farooq'''
_A : Tuple ='''contact@muhammad... | 631 |
'''simple docstring'''
_A : List[str] ='''0.21.0'''
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_di... | 631 | 1 |
'''simple docstring'''
def a_ ( __snake_case : str , __snake_case : str ) -> int:
"""simple docstring"""
if len(__snake_case ) != len(__snake_case ):
raise ValueError('''String lengths must match!''' )
lowerCamelCase_ =0
for chara, ... | 676 |
'''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_... | 8 | 0 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def SCREAMING_SNAKE_CASE__ ( ) -> List[str]:
_lowercase = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
_lowercase = parser.add_subparsers(he... | 535 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case = {
"""configuration_ber... | 535 | 1 |
"""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 (... | 584 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_ ( SCREAMING_SNAKE_CASE : list[int | str] ):
'''simple docstring'''
create_state_space_tree(SCREAMING_SNAKE_CASE , [] , 0 , [0 for i in r... | 179 | 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 a... | 707 | from __future__ import annotations
from collections.abc import MutableSequence
class __lowercase :
def __init__( self : Optional[Any] , __lowerCamelCase : int , __lowerCamelCase : MutableSequence[float] ) -> None:
'... | 479 | 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 UpperCAmelCase ( UpperCAmelCase__ : List[str] ... | 320 |
'''simple docstring'''
def __snake_case ( lowercase : int = 1_000_000 ):
snake_case_ = set(range(3 , lowercase , 2 ) )
primes.add(2 )
for p in range(3 , lowercase , 2 ):
if p not in primes:
continue
primes.difference_updat... | 508 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCa... | 5 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A : int = logging.get_logger(__name__)
A : Optional[int] = {
"facebook/xmod-base": "https://huggin... | 5 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
Conditional... | 528 | """simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class snake_case__ ( unittest.TestCase ):
def a__ ( self ):
__a = [
"safety_checker/pytorch_model.bin",
"safety_checker/mod... | 528 | 1 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCamelCase ( nn.Module ):
"""simple docstring"""
snake_case = 4_2
sna... | 700 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def snake_case ( UpperCAmelCase : List[Any] ):
if "model" in orig_key:
A = orig_key.replace('model.', '' )
if "norm1" in orig_key:
A = orig_key.replace('norm1'... | 110 | 0 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRConte... | 462 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_utils import i... | 462 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
"""andreasmadsen/efficien... | 718 |
"""simple docstring"""
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 ShapERende... | 349 | 0 |
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_mo... | 39 |
"""simple docstring"""
import operator
def snake_case ( lowerCAmelCase_ , lowerCAmelCase_ = False , lowerCAmelCase_ = None ) -> list:
_snake_case = operator.lt if reverse else operator.gt
_snake_case = solution or []
if not arr:
retu... | 103 | 0 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def __lowercase( __snake_case : Union[str, Any] ) -> Union[str, Any]:
return x + 2
class _lowerCamelCase (unittest.TestCase ):
def __... | 345 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_an... | 345 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
print("\nThe shortest path matrix using Floyd Warshall algorithm\n" )
for i in range(_a ):
for j in range(_a ):
if dist[i][j] != float("inf" ):
... | 682 |
"""simple docstring"""
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
UpperCAmelCase =get_tests_... | 617 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDI... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 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 transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel... | 247 |
"""simple docstring"""
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def UpperCAmelCase ( snake_case : BertModel , snake_case : str , snake_case : str ):
_lowerCAmelCa... | 227 | 0 |
'''simple docstring'''
_snake_case : Dict = {
"""A""": """.-""", """B""": """-...""", """C""": """-.-.""", """D""": """-..""", """E""": """.""", """F""": """..-.""", """G""": """--.""",
"""H""": """....""", """I""": """..""", """J""": """.---""", """K""": """-.-""", """L""": """.-..""", """M... | 493 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_snake_case : List[Any] = logging.get_logger(__name__)
class lowerCAmelCase ( __UpperCAmelCase ):
def __init__( self , *UpperCamelCase , **U... | 493 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: List[str] ) -> Any:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : str = set({"(", "[", "{"} )
__lowerCamelCase : List[str] = set({")", "]", "}"} )... | 646 |
"""simple docstring"""
class lowerCAmelCase__ :
def __init__( self , UpperCamelCase__ , UpperCamelCase__=None , UpperCamelCase__=None ):
'''simple docstring'''
A__ = data
A__ = previous
A__ = next_node
def __str__( s... | 337 | 0 |
'''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,
DistilBertConfig,
DistilBe... | 257 | '''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from... | 257 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__A = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig"""... | 93 |
"""simple docstring"""
def __A (_SCREAMING_SNAKE_CASE ) ->str:
"""simple docstring"""
lowerCAmelCase__ :List[Any] = int(_SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(_SCREAMING_SNAKE_CASE )
lowerCAmelCase__ ... | 93 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowercase = logging.get_logger(__name__)
lowercase = {
'''google/umt5-small''': ''... | 24 |
"""simple docstring"""
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCa... | 24 | 1 |
'''simple docstring'''
import math
import os
import sys
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Union[str, Any] = ''
try:
with open(_A , 'rb' ) as bina... | 444 |
'''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,
)
lowerCAmelCase : int ... | 444 | 1 |
'''simple docstring'''
UpperCAmelCase = [0, 2, 4, 6, 8]
UpperCAmelCase = [1, 3, 5, 7, 9]
def __lowerCAmelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )-> int:
"""simple docstring"""
... | 720 |
def __lowerCAmelCase (SCREAMING_SNAKE_CASE = 3 , SCREAMING_SNAKE_CASE = 7 , SCREAMING_SNAKE_CASE = 100_0000 )-> int:
"""simple docstring"""
snake_case_ = 0
snake_case_ = 1
for current_denominator in range(1 , limit + 1 ):
... | 531 | 0 |
'''simple docstring'''
def _a (lowercase__ : int , lowercase__ : int ) -> float:
"""simple docstring"""
return base * power(lowercase__ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print("Raise base to the power of exponent usi... | 56 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Optional[int] =logging.get_logger(__name__)
_UpperCamelCase : Tuple ={
'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
# See all CAN... | 206 | 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... | 705 |
import numpy as np
def lowerCAmelCase_ ( lowerCamelCase , lowerCamelCase , lowerCamelCase = 1E-12 , lowerCamelCase = 100 , ):
assert np.shape(lowerCamelCase )[0] == np.shape(lowerCamelCase )[1]
# Ensure proper dimensionality.
assert np.shape(lowerCamelCase )[0... | 367 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import Backbon... | 195 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : List[str] = 3
_UpperCamelCase : Any = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 1_5 == 0:
... | 195 | 1 |
"""simple docstring"""
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 Optio... | 16 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_... | 486 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependency... | 633 | 0 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tens... | 718 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class _lowercase :
def __init__( self , A__ ) -> None:
snake_case = value
snake_case = None
snake_case = None
cla... | 44 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
'google/fnet-large': 'https://huggin... | 322 |
import argparse
import json
from tqdm import tqdm
def UpperCamelCase__ ( ) -> Union[str, Any]:
'''simple docstring'''
_lowercase : int = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_path''' ,... | 322 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
UpperCamelCase__ = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that ge... | 717 |
"""simple docstring"""
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 254 | 0 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 598 |
'''simple docstring'''
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
... | 267 | 0 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ : int ) -> bool:
__a = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowercase ( lowerCAmelCase__ : int = 5000 ) -> int:
__a = [(i * (3 * i - 1)) // 2 for i in range(1 , ... | 702 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def lowercase ( lowerCAmelCase__ : Optiona... | 65 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
... | 502 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['torch', 'transformers', 'onnx']
def __init__( self: Union[str, Any]... | 293 | 0 |
import os
from collections.abc import Iterator
def lowerCamelCase__ ( UpperCamelCase__ : str = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(UpperCamelCase__ ):
_snake_case = [d for d in dir... | 541 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ = {"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}
try:
if not is_torch_ava... | 541 | 1 |
def lowerCamelCase__ ( a : int ) -> int:
"""simple docstring"""
a__ :int = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCamelCase__ ( a : int = 5_000 ) -> int:
"""simple docstring"""
a__ :int = ... | 395 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'''studio-ousia/luke-base''': '''https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json''',
'''studio-ousia/luke-large''': '''h... | 164 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, sl... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
a_ = logging.get_logger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
f... | 694 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import ... | 694 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pr... | 283 | """simple docstring"""
def __lowerCAmelCase( __UpperCAmelCase ):
"""simple docstring"""
stooge(__UpperCAmelCase ,0 ,len(__UpperCAmelCase ) - 1 )
return arr
def __lowerCAmelCase( __UpperCAmelCase ,__UpperCAmelCase ,__UpperCAmelCase ):
"""simple docstring"... | 283 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ : List[Any] = logging.get_logger(__name__)
lowerCamelCase__ ... | 31 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__lowercase ... | 203 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _lowerCAmelCase :
def __init__( self , UpperCamelCase__ ) -> Optional[int]:
'''simple docstring'''
snake_case : list[dict] = []
self.adlist.appe... | 117 |
"""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
fr... | 117 | 1 |
'''simple docstring'''
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 ModelT... | 5 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self... | 5 | 1 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
A_ : Any = (7_20, 12_80) # Height, Width
A_ : List[Any] = (0.4, 0.6) # if height or width lower than this scale, drop it.
A_ : ... | 696 |
"""simple docstring"""
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
... | 696 | 1 |
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 =... | 99 |
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_... | 243 | 0 |
"""simple docstring"""
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def Upper... | 706 | """simple docstring"""
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class UpperCamel... | 536 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_: Union[str, Any] =logging.get_logger(__name__)
SCREAMING_... | 78 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a_ = get_tests_dir("""fixtures/spie... | 177 | 0 |
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from ...utils import logging
... | 433 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_t... | 433 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_a... | 131 |
"""simple docstring"""
import qiskit
def lowerCamelCase_ (UpperCamelCase__ : int , UpperCamelCase__ : int ):
_UpperCAmelCase : Any = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
_UpperCAmelC... | 506 | 0 |
import os
from datetime import datetime as dt
from github import Github
lowercase : Optional[Any] = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]... | 703 |
class __lowercase :
"""simple docstring"""
def __init__( self ) -> Optional[Any]:
A : Tuple = {}
def snake_case ( self ) -> None:
print(self.vertex )
for i in self.vertex:
... | 423 | 0 |
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