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 sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
lowercase : Union[str, Any] = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={W... | 302 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 302 | 1 |
"""simple docstring"""
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... | 716 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def a__ ( lowerCAmelCase : List[str] ):
'''simple docstring'''
def wrapper(*lowerCAmelCase : Any , ... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( snake_case_ :int ):
__UpperCAmelCase = [True] * limit
__UpperCAmelCase = False
__UpperCAmelCase = False
__UpperCAmelCase = True
for i in range(3 , int(limi... | 49 |
from __future__ import annotations
lowerCAmelCase__ : Union[str, Any] =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( A__, A__, A__, A__, A__, ):
SCREAMING_SNAKE_CASE_ : List[Any] = ... | 101 | 0 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_snake_case = 10
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _l... | 708 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len(_lowerCamelCase )
for i in range(1 , _lowerCamelCase ):
_lowerCAmelCase : List[Any] = collection[i]
... | 658 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class UpperCAmelCase ( __snake_case ):
def __init__( self ... | 386 |
def __lowerCamelCase ( _lowercase ) -> list:
for i in range(len(_lowercase ) - 1 , 0 , -1 ):
UpperCamelCase = False
for j in range(_lowercase , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
... | 282 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
_lowerCAmelCase : List[str] = f"""Input value of [number={number}] must be an integer"""
raise Type... | 16 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 1 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
__A = TypeVar("""T""")
__A = Union[List[T], Tuple[T, ...]]
__A = Union[T, List[T], Dict[str, T]]
__A = Union[str, bytes, os.PathLike]
| 93 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
_lowercase = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
_lowercase = _LazyModule(__name__, globals()['''__file__'''... | 659 | 0 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 113 |
'''simple docstring'''
import os
def _UpperCamelCase ( UpperCamelCase__ = "input.txt" ):
with open(os.path.join(os.path.dirname(UpperCamelCase__ ) , UpperCamelCase__ ) ) as input_file:
UpperCAmelCase__ : Tuple = [
[int(Up... | 113 | 1 |
from __future__ import annotations
from math import pi
def _a ( lowercase__ : float , lowercase__ : float , lowercase__ : float ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('One and only one argument... | 85 |
"""simple docstring"""
from math import sqrt
def UpperCAmelCase ( A : int = 100_0000 ):
'''simple docstring'''
_UpperCAmelCase = 0
_UpperCAmelCase = 0
_UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
... | 573 | 0 |
"""simple docstring"""
__UpperCAmelCase ={
"""A""": """.-""", """B""": """-...""", """C""": """-.-.""", """D""": """-..""", """E""": """.""", """F""": """..-.""", """G""": """--.""",
"""H""": """....""", """I""": """..""", """J""": """.---""", """K""": """-.-""", """L""": """.-..""", "... | 712 |
"""simple docstring"""
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase =logging.get_logger(__name__)
__UpperCAmelCase =... | 261 | 0 |
from __future__ import annotations
__a = list[list[int]]
# assigning initial values to the grid
__a = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0, 5],
[0, 5, 0, ... | 30 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
BertTokenizerFast,
... | 30 | 1 |
import argparse
import os
import re
import packaging.version
_lowercase = "examples/"
_lowercase = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=\s+\"([^\"]+)\"\s*$", re.MULTILINE)... | 713 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def lowerCAmelCase__ ( UpperCamelCase_ : dict )-> tuple:
... | 526 | 0 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class lowerCAmelCase_ :
_UpperCamelCase : Dict = 42
_UpperCamelCa... | 66 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 | 0 |
from __future__ import annotations
a_ : Optional[Any] = 'Muhammad Umer Farooq'
a_ : List[Any] = 'MIT'
a_ : Optional[Any] = '1.0.0'
a_ : List[Any] = 'Muhammad Umer Farooq'
a_ : Union[str, Any] = 'contact@muhammadumerfarooq.me'
a_ : Optio... | 148 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, 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
from ...test_pipeline_mixin im... | 148 | 1 |
'''simple docstring'''
def UpperCamelCase_ ( A__ : int ):
'''simple docstring'''
if not isinstance(A__ , A__ ):
raise ValueError("""check_bouncy() accepts only integer arguments""" )
lowerCAmelCase_ : Any = str(A__ )
lowerCAmelC... | 275 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__A : Union[str, Any] = TypeVar("KEY")
__A : Union[str, Any] = TypeVar("VAL")
@dataclass(frozen=_SCREAMING... | 275 | 1 |
"""simple docstring"""
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 ConfigTest... | 210 |
"""simple docstring"""
def UpperCamelCase ( UpperCAmelCase ) ->bool:
"""simple docstring"""
a_ = 0
for ch in input_str:
a_ = ord(UpperCAmelCase )
a_ = pow(2 , UpperCAmelCase )
# If we already turned on bit for current character's... | 210 | 1 |
import inspect
import unittest
from transformers import MobileNetVaConfig
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 ...te... | 35 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
a_ :List[Any] = logging.getLogger(__name__)
@dataclass
class ... | 35 | 1 |
"""simple docstring"""
import math
def lowercase_ ( _snake_case ):
if not isinstance(_lowerCAmelCase ,_lowerCAmelCase ):
SCREAMING_SNAKE_CASE__ : List[Any] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(_lowerCAmelCase )
... | 716 |
"""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
... | 545 | 0 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> list:
'''simple docstring'''
if any(not isinstance(__snake_case , __snake_case ) or x < 0 for x in sequence ):
raise TypeError("""Sequence must be list of non-negative integers""" )
for ... | 109 |
"""simple docstring"""
def A ( __snake_case: str ) -> list:
"""simple docstring"""
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(__snake_case ) )
if txt[a].isalpha()
]
if __name__ == "... | 545 | 0 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def snake_case__ ( UpperCAmelCase : Optional[int] ):
lowerCAmelCase__ :List[Any] = args.pruning_method
lowerCAmelCase__ ... | 704 |
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
_a : Tuple = logging.get_logger(__name__)
_a : Optional[int] = {
"""fac... | 111 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipe... | 103 |
# 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 app... | 336 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( UpperCamelCase_ ):
@staticmethod
@abstractmethod
def lowercase_ ( UpperCamelCase__ ):
'''simple docstring'''
r... | 712 |
"""simple docstring"""
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase =logging.get_logger(__name__)
__UpperCAmelCase =... | 261 | 0 |
"""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_video_inputs
if is_... | 264 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional impo... | 282 | 0 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYaaagf
... | 714 | 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 models at https://huggingface.co/models?f... | 286 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_a = logging.get_logger(__name__)
_a = {
"""shi-labs/nat-mini-in... | 19 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils ... | 319 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, ... | 718 | '''simple docstring'''
lowercase_ = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/tran... | 58 | 0 |
from __future__ import annotations
def a_ ( lowerCAmelCase_ : list[int], lowerCAmelCase_ : int, lowerCAmelCase_ : int, lowerCAmelCase_ : int ):
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[indexa] < array[indexa]
... | 53 |
'''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
_UpperCamelCase = logging.get_logger(__name__)
_UpperCam... | 111 | 0 |
'''simple docstring'''
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
_A : Optional[Any] = datasets.utils.logging.get_logger(__name__)
class _lowercase ( folder_... | 330 | '''simple docstring'''
from ...processing_utils import ProcessorMixin
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
_SCREAMING_SNAKE_CASE : str = """WhisperFeatureExtractor"""
_SCREAMING_SNAKE_CASE : Any = """WhisperTokenizer... | 330 | 1 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase = None , __lo... | 23 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
UpperCAmelCase =... | 84 | 0 |
import os
def lowerCamelCase__ ( ):
'''simple docstring'''
snake_case_ = os.path.join(os.path.dirname(_A ) , "num.txt" )
with open(_A ) as file_hand:
return str(sum(int(_A ) for line in file_hand ) )[:10]
if __name__... | 139 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class UpperCAmelCase ( UpperCAmelCase__ ):
'''simple... | 139 | 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
snake_case = {
# 1536-bit
5: {
"""prime""": int(
... | 67 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_lowerCAmelCase = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''enhancement''',
'''new pipeline/model''',
'''new scheduler''',
'''wip''',
]
de... | 565 | 0 |
from ...processing_utils import ProcessorMixin
class a (_lowerCAmelCase ):
"""simple docstring"""
__UpperCAmelCase : Any = "SpeechT5FeatureExtractor"
__UpperCAmelCase : Union[str, Any] = "SpeechT5Tokenizer"
def __init__( s... | 203 |
import unittest
import numpy as np
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase = None , ):
__snake_case : List[str] = np.shape(__lowerCamelCase )
__snake_case : Optional[Any] ... | 203 | 1 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def A_ ( _lowerCAmelCase ) -> list[list[float]]:
UpperCamelCase : List[str] = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for ... | 629 |
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
__lo... | 629 | 1 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenc... | 718 |
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
if is_torch... | 84 | 0 |
import numpy
# List of input, output pairs
A_ : Any = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
A_ : List[Any] = (((515, 22, 13), 555), ((61, 35, 49), 150))
A_ : ... | 57 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {
'configuration_deberta': ['DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Debe... | 665 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
_lowercase = logging.get_logger(__name__)
_lowercase = {'''... | 714 |
from __future__ import annotations
from random import random
class __snake_case :
"""simple docstring"""
def __init__( self : Optional[int] ,lowerCAmelCase__ : int | None = None ) -> int:
'''simple docstring'''
lowerCAmelCase_ : Dict ... | 683 | 0 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
lowerCamelCase_ = ''''''
lowerCamelCase_ = ''''''
lowerCamelCase_ = ''''''
lowerCamelCase_ = 1 # (0 is vertical, 1 is horizontal)
def __magic_name__ ( ):
'''simple docstring... | 513 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase_ = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''InstructBlipQFormerConfig'''... | 513 | 1 |
import math
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> list:
'''simple docstring'''
SCREAMING_SNAKE_CASE = [True] * n
SCREAMING_SNAKE_CASE = False
SCREAMING_SNAKE_CASE = False
SCREAMING_SNAKE_CASE = True
for i in range(3 ... | 116 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_D... | 116 | 1 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
UpperCAmelCase : List[str] = version.parse(importlib_metadata.version("""nltk"""))
if NLTK_VERSION >= version.Version("""3.6.4"""):
from nltk ... | 563 |
from itertools import count
def _A ( SCREAMING_SNAKE_CASE : int = 50 ):
"""simple docstring"""
a__ : Union[str, Any] =[1] * min_block_length
for n in count(SCREAMING_SNAKE_CASE ):
fill_count_functions.append(1 )
for block_length in range(SCREAM... | 563 | 1 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
UpperCamelCase_ = (
"4S 3H 2C 7S 5H",
"9D 8H 2C 6S 7H",
"2D 6D 9D TH 7D",
"TC 8C 2S JH 6C",
"JH 8S TH AH QH",
"TS KS 5S 9S AC",
"KD 6S 9D TH AD",
"KS ... | 712 |
def lowerCamelCase_ ( _a : list ):
'''simple docstring'''
for i in range(len(_a ) - 1 , 0 , -1 ):
UpperCAmelCase_ : Optional[int] = False
for j in range(_a , 0 , -1 ):
if unsorted[j] < unsorted[j ... | 322 | 0 |
'''simple docstring'''
import argparse
from collections import defaultdict
def lowercase_ ( __A : Optional[Any] , __A : Optional[int] , __A : str , __A : Tuple , __A : int ) -> Dict:
"""simple docstring"""
... | 94 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_c... | 94 | 1 |
import fire
from utils import calculate_rouge, save_json
def __A ( _lowercase , _lowercase , _lowercase=None , **_lowercase ):
'''simple docstring'''
_A = [x.strip() for x in open(_lowercase ).readlines()]
_A = [x.strip() for x in open(_lowerc... | 700 |
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
__A = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
... | 62 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ : List[str] ) -> Dict:
# This defines a "chinese character" as anything in the CJK Unicode block:
... | 287 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ : int = 2_00_00_00 ) -> int:
_lowercase = [0 for i in range(n + 1 )]
_lowercase = 1
_lowercase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_lis... | 287 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
),
... | 715 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 0 |
"""simple docstring"""
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _a ( yaml.SafeLoader):
def __lowercase ( self : List[Any] , _lowercase : Dict ) -> Union[str, Any]... | 449 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
A = {'configuration_vit': ['VIT_PRETRAINED_CONFIG... | 449 | 1 |
from collections.abc import Sequence
from queue import Queue
class _snake_case :
def __init__( self ,UpperCamelCase ,UpperCamelCase ,UpperCamelCase ,UpperCamelCase=None ,UpperCamelCase=None ) -> Tuple:
snake_case__ :Any = ... | 57 |
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:
fro... | 57 | 1 |
'''simple docstring'''
def lowerCamelCase__ ( _A ):
return credit_card_number.startswith(('34', '35', '37', '4', '5', '6') )
def lowerCamelCase__ ( _A ):
a : Optional[int] = credit_card_number
a : List[Any] = 0
a : Tuple = len(_A ) - 2
for i in range(_A... | 526 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase: List[str] = logging.get_logger(__name__)
lowerCAmelCase: int = {
'bert-bas... | 526 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowercase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa... | 704 |
'''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/LIC... | 695 | 0 |
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 __lowercase ( __snake_case ):
UpperCam... | 377 |
import argparse
import os
import re
import packaging.version
__a = """examples/"""
__a = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compile(R"""^__version__\s+=\s+\"([^\"]+)\"\s... | 377 | 1 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase : List[Any] ... | 706 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
... | 651 | 0 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .... | 44 |
'''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, AutoTo... | 44 | 1 |
"""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,
Di... | 529 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_... | 529 | 1 |
from __future__ import annotations
def _lowerCAmelCase ( __lowerCAmelCase , __lowerCAmelCase ) -> Union[str, Any]:
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1 or n <= 1:
return
insert_next(lowerCamelCase__ , n - 1 )
rec_insertion_sort... | 252 |
'''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
fr... | 131 | 0 |
"""simple docstring"""
import math
UpperCamelCase_ : Optional[int] = 10
UpperCamelCase_ : int = 7
UpperCamelCase_ : List[Any] = BALLS_PER_COLOUR * NUM_COLOURS
def __lowercase ( a : int = 20 ) -> Any:
__snake_case : Dict =math.co... | 705 |
"""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
UpperCamelCase_ : Optional[Any] = logging.get_logger(__n... | 497 | 0 |
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 43 |
class _a :
def __init__( self: Tuple , UpperCamelCase_: Dict ) -> List[str]:
"""simple docstring"""
lowercase__ = val
lowercase__ = None
lowercase__ = None
def lowerCamelCase_ ( ... | 43 | 1 |
"""simple docstring"""
class _SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self: Optional[int] , __A: str = "" , __A: bool = False ):
'''simple docstring'''
a__ = {}
# A node will b... | 200 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( lowerCamelCase_):
assert column_title.isupper()
a__ = 0
a__ = len(lowerCamelCase_) - 1
a__ = 0
while index >= 0:
a__ = (ord(column_title[index]) - 64) * pow(26 , ... | 200 | 1 |
'''simple docstring'''
def __lowercase (_SCREAMING_SNAKE_CASE :list[list[int | float]] ):
SCREAMING_SNAKE_CASE : Any = len(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE : Optional[Any] = len(matrix[0] )
SCREAMING_SNAKE_CASE : int = min(_SC... | 507 |
'''simple docstring'''
def __lowercase (_SCREAMING_SNAKE_CASE :int , _SCREAMING_SNAKE_CASE :int ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 507 | 1 |
"""simple docstring"""
__lowercase = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.60_93_44,
"knot": 1.8_52,
}
__lowercase = {
"km/h": 1.0,
"m/s": 0.2_77_77_77_78,
"mph": 0.6_21_37_11_92,
"knot": 0.5_39_95_68_03,
}
def lowerCAmelCase (__UpperC... | 296 | """simple docstring"""
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
__lowercase = logging.get_logger(__name__)
def lowe... | 296 | 1 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def __UpperCamelCase (_SCREAMING_SNAKE_CASE = "laptop" ) -> DataFrame:
lowercase__ = F"""https://www.amazon.in/laptop/s?k={product}"""
lowercase__... | 235 |
# 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
#
# Unl... | 235 | 1 |
import os
import sys
import unittest
lowercase : Tuple = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_... | 704 | from __future__ import annotations
lowercase : Optional[int] = [True] * 1_0_0_0_0_0_1
lowercase : Tuple = 2
while i * i <= 1_0_0_0_0_0_0:
if seive[i]:
for j in range(i * i, 1_0_0_0_0_0_1, i):
lowercase : int = False
i += 1
def Upper... | 584 | 0 |
from functools import reduce
UpperCAmelCase_ = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"... | 2 |
'''simple docstring'''
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 .tokenizatio... | 365 | 0 |
"""simple docstring"""
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
__lowerCAmelCase : Tuple = datasets.logging.get_logger(__name__)
__lowerCA... | 21 |
"""simple docstring"""
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__lowerCAmelCase : List[str] = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for Gen... | 21 | 1 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
UpperCAmelCase__ : Union[str, Any] = True
except (ImportError, ModuleNotFoundError):
UpperCAmelCase__ : Tuple = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", qui... | 48 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def snake_case_ ( lowerCAmelCase_ : ndarray ):
return np.dot(lowerCAmelCase_ , lowerCAmelCase_ )
class lowerCAmelCase :
'''simple docstring'''
def __init... | 149 | 0 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('''Googling.....''')
lowerCamelCase__ = '''https://www.google.com/search?q=''' + ''' '''.join(sys.argv[1:])
lowerCamelCase__ = requests.g... | 226 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class __magic_name__ (__lowercase ):
lowerCamelCase__ = ''''''
lowerCamelCase__ = (
None # protocol passed in prefix to the ur... | 226 | 1 |
"""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, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ :Union[str, Any] = logging.get_... | 355 |
"""simple docstring"""
import warnings
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 c... | 355 | 1 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 716 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__UpperCAmelCase : Any = 0B1_0_1_1_0_0_1_1_1_1_1_0_1_1_0_0_1_0_0_1_0_0_0_0_0_1_1... | 249 | 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():
impor... | 2 | '''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTok... | 494 | 0 |
"""simple docstring"""
from math import factorial
def __a ( _lowercase = 100 ):
"""simple docstring"""
return sum(map(_lowercase , str(factorial(_lowercase ) ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the Number: ").strip())))
| 121 | """simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
UpperCAmelCase : Dict = False
class __SCREAMING_SNAKE_C... | 121 | 1 |
"""simple docstring"""
def UpperCAmelCase_ ( __a : Dict , __a : str ):
'''simple docstring'''
_lowerCamelCase : int = ''
for i in table:
res += inp[i - 1]
return res
def UpperCAmelCase_ ( __a : Any ):
''... | 437 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
a_ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
a_ = re.compile(r"""([a-z\d])([A-Z])""")
a_ = re.compile(r"""(?<!_)_(?!_)""")
a_ = re.compile(r"""(_{2,})""")
a_ = r"""^\w+(\.\w+)*$"""
... | 437 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassification,
Data... | 37 |
import math
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(SCREAMING_SNAKE_CASE_ )
else:
if x == 0: # 0 raised to any number is 0
return 0... | 37 | 1 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase__ =logging.get_logger(__name__)
UpperCAmelCase__ ={
"vocab_file": "vocab.json",
"tokeni... | 616 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def lowerCAmelCase_ ( ):
"""simple docstring"""
wit... | 616 | 1 |
'''simple docstring'''
import heapq
import sys
import numpy as np
snake_case = tuple[int, int]
class lowerCAmelCase :
def __init__( self : Dict ):
'''simple docstring'''
lowerCAmelCase__ : List[str] = []
lowerCAmelCase__ : List[str] =... | 568 |
'''simple docstring'''
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 568 | 1 |
from __future__ import annotations
from collections.abc import Callable
__UpperCamelCase : List[str] = list[list[float | int]]
def _UpperCAmelCase ( UpperCAmelCase : Matrix , UpperCAmelCase : Matrix ):
"""simple docstring"""
__lower... | 519 |
from __future__ import annotations
def _UpperCAmelCase ( UpperCAmelCase : str , UpperCAmelCase : str ):
"""simple docstring"""
__lowerCamelCase : int = get_failure_array(UpperCAmelCase )
# 2) Step through text searching fo... | 519 | 1 |
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
UpperCamelCase = TypeVar('KT')
UpperCamelCase = TypeVar('VT')
class _a ( Generic[KT, VT] ):
'''simple docstring'''
def __init__( self , __UpperCAmelCase = "ro... | 706 | import os
import string
import sys
UpperCamelCase = 1 << 8
UpperCamelCase = {
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,
'left': 68 + ARROW_KEY_FLAG,
'mod_int... | 387 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/GP... | 31 |
UpperCAmelCase__ = '''Input must be a string of 8 numbers plus letter'''
UpperCAmelCase__ = '''TRWAGMYFPDXBNJZSQVHLCKE'''
def a_ (__A ) -> bool:
"""simple docstring"""
if not isinstance(__A , __A ):
__a : Any ... | 351 | 0 |
import math
def A_ ( a , a ):
"""simple docstring"""
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(a )
else:
if x == 0: # 0 raised to any number is 0
return 0
... | 353 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def A_ ( a , a , a ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : int = TaConfig.from... | 353 | 1 |
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_avai... | 27 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
lowercase_ = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__( self , *A , **A ) ... | 314 | 0 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
_UpperCamelCase : List[Any] =50000
_UpperCamelCase : Dict =5000
_UpperCamelCase : List[Any] =os.path.split(__file__)
_UpperCamelCase : Union[str, Any] =os.path.join(RE... | 702 |
from ...configuration_utils import PretrainedConfig
_UpperCamelCase : Tuple ={
'google/tapas-base-finetuned-sqa': (
'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
),
'google/tapas-base-finetuned-wtq': (
'https://huggingface.co/goo... | 332 | 0 |
"""simple docstring"""
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
fr... | 65 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
A_ : int = input('Enter image url: ').strip()
print(F"""Downloading image from {url} ...""")
A_ : Dict = BeautifulSoup(requests.get(url).content, 'html.pa... | 303 | 0 |
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class a ... | 83 | _SCREAMING_SNAKE_CASE = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', 'U': '..-',
'V': '...-'... | 83 | 1 |
# 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 ... | 62 | '''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
_UpperCAmelCase : List[Any] = False
class lowercase_ ... | 107 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torc... | 41 |
'''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 | 1 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 10_00 ):
"""simple docstring"""
return sum(e for e in range(3 ,__UpperCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 28 |
import requests
from bsa import BeautifulSoup
def lowerCamelCase( a__ = "https://www.worldometers.info/coronavirus"):
_SCREAMING_SNAKE_CASE =BeautifulSoup(requests.get(a__).text ,'''html.parser''')
_SCREAMING_SNAKE_CASE =soup.findAll('''h1''')
_SCREAMING_SNAKE_CASE =soup... | 691 | 0 |
'''simple docstring'''
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTeste... | 581 |
'''simple docstring'''
from __future__ import annotations
def a ( UpperCamelCase_ : list[float] , UpperCamelCase_ : list[float] ) -> float:
snake_case__ =sorted(numsa + numsa )
snake_case__ , snake_case__ =divmod(len(UpperCamelCase_ ) , 2 )
... | 581 | 1 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import Scheduler... | 334 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
__A : List[Any] = {
'facebook/maskformer-swin-ba... | 334 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''shi-labs/nat-mini-in1k-... | 714 |
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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNA... | 52 | 0 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=snake_case_ )
class UpperCamelCase ( snake_case_ ):
U... | 389 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class UpperCamelCase ( snake_case_ ):
def __init__( self : List[Any] , UpperCAmelCase__ : str , UpperCAmelCase__ : Optional[int] ) -> str:
super().__i... | 389 | 1 |
def a ( A__ : str , A__ : int ) -> list[str]:
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(A__ ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
testmod()
| 380 |
from __future__ import annotations
from typing import Any
class __lowerCAmelCase :
def __init__( self , lowerCAmelCase ) -> None:
'''simple docstring'''
_lowercase =num_of_nodes
_lowercase =[]
_lowercase... | 380 | 1 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class _a ( datasets.BeamBasedBuilder ):
"""simple docstring"""
... | 23 |
a__ = [0, 2, 4, 6, 8]
a__ = [1, 3, 5, 7, 9]
def _UpperCAmelCase ( a : int , a : int , a : list[int] , a : int ):
if remaining_length == 0:
if digits[0] == 0 or digits[-1] == 0:
return 0
for i ... | 654 | 0 |
"""simple docstring"""
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 Con... | 579 |
"""simple docstring"""
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 im... | 579 | 1 |
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:
from ..utils.dummy_pt_ob... | 194 |
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
a_ : Optional[int] = '.'
# Internal TensorFlow ops that ... | 194 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: int ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(0 ) == 0 )
def lowerCAmelCase__ ( ) -> None:
'''simple docstring'''
... | 626 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[list[str]] , SCREAMING_SNAKE_CASE_: int , ) -> ... | 626 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : List[str] = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https... | 102 |
def _lowercase ( a__ : list ) -> list:
"""simple docstring"""
if any(not isinstance(a__ , a__ ) or x < 0 for x in sequence ):
raise TypeError("Sequence must be list of non-negative integers" )
for _ in range(len(a__ ) ):
for i, (rod_upper, rod_lower) ... | 147 | 0 |
from numpy import exp, pi, sqrt
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0.0 ,lowerCAmelCase__ = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 72 |
# using dfs for finding eulerian path traversal
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__=None ):
lowercase = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
lowercase , l... | 72 | 1 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __snake_case ( _lowercase):
snake_case__ : Any = (DDPMScheduler,)
def SCREAMING_SNAKE_CASE ( self : str , **__lowerCAmelCase ... | 83 | """simple docstring"""
SCREAMING_SNAKE_CASE__ : Dict =[
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
... | 434 | 0 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWit... | 31 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from d... | 31 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
log... | 279 |
"""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... | 674 | 0 |
# Copyright 2021 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
#
# Unles... | 708 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenizati... | 559 | 0 |
from math import isclose, sqrt
def lowerCAmelCase ( UpperCamelCase__ : float , UpperCamelCase__ : float , UpperCamelCase__ : float ) -> tuple[float, float, float]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: Tuple = point_y / 4 /... | 202 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCAmelCase ( UpperCamelCase__ : Union[str, Any] ) -> int:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: List[Any] ... | 202 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_... | 18 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase__ : Optional[Any] = {
"configuration_funnel": ["FUNNEL_PRETRAINED... | 18 | 1 |
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