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'''
lowercase : Optional[int] = '0.18.2'
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is... | 649 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase : Optional[Any] = {'configuration_reformer': ['REFOR... | 649 | 1 |
'''simple docstring'''
import numpy as np
a__ : int = [
['a', 'b', 'c', 'd', 'e'],
['f', 'g', 'h', 'i', 'k'],
['l', 'm', 'n', 'o', 'p'],
['q', 'r', 's', 't', 'u'],
['v', 'w', 'x', 'y', 'z'],
]
class lowerCAmelCase__ :
'''simple docstring'''
def __init__... | 715 |
'''simple docstring'''
def __snake_case ( ) -> List[Any]:
"""simple docstring"""
for n in range(1 , 1_000_000 ):
yield n * (n + 1) // 2
def __snake_case ( SCREAMING_SNAKE_CASE_ : Optional[Any] ) -> List[Any]:
"""simple docstring"""
... | 570 | 0 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
lowerCamelCase = """\
@inproceedings{popovic-2015-chrf,
title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",
author = \"Popovi{\'c}, ... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float(moles / volume ) * nfactor )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float((moles * 0... | 82 | 1 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.n... | 105 |
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Optional[int] = logging.get_logge... | 105 | 1 |
import unittest
from knapsack import knapsack as k
class a (unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self : List[str] ) -> Dict:
__snake_case : Any = 0
__snake_case : List[... | 81 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
Dat... | 691 | 0 |
'''simple docstring'''
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 : List[Any] = {
'xlm-mlm-en-2... | 707 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
A : Optional[Any] = {'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'De... | 273 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
__A = logging.get_logger(__name__)
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase ... | 586 | """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 = {
"distilbert-base-uncased": "https://huggingfa... | 586 | 1 |
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configu... | 718 | """simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokeni... | 67 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://e... | 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 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def lowerCAmelCase_( lowercase_ : Tuple ) -> Optional[int]:
return choice(lowercase_ )
def lowerCAmelCase_( lowercase_ : list[int] , lowercase_ : in... | 712 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Optional[Any] = {
'''configuration_vision_encoder_decoder''':... | 623 | 0 |
import collections
import importlib.util
import os
import re
from pathlib import Path
__A ='''src/transformers'''
# Matches is_xxx_available()
__A =re.compile(R'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
__A =re.compile(R'''^_import_structure\s+=\s+\{([^\}]+)\}'''... | 463 |
from math import isqrt
def lowerCamelCase_ ( lowerCamelCase__ ):
lowerCamelCase_ = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowerCamelCase__ , lower... | 463 | 1 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a__ ( _SCREAMING_SNAKE_CASE = 3 ):
"""simple docstring"""
if isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE )... | 544 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 544 | 1 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_availa... | 193 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class __snake_case ( ... | 193 | 1 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer, DPRQ... | 279 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}
class _lowerCAmelCase ( __a ):
_lowercase ='''transfo-xl'''
_lo... | 279 | 1 |
from __future__ import annotations
def UpperCamelCase ( _A ):
"""simple docstring"""
if len(_A ) == 0:
return []
__magic_name__ ,__magic_name__ : Tuple = min(_A ), max(_A )
__magic_name__ : int = int(max_value - min_... | 324 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPanoramaPipeline,
... | 324 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
lowerCAmelCase__ ... | 707 |
"""simple docstring"""
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def a__ ( _SCREAMING_SNAKE_CASE ): # picklable for... | 544 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ : Tuple = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
try:
if not is_torch_availab... | 713 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple reposi... | 444 | 0 |
def A ( _SCREAMING_SNAKE_CASE ) -> Any:
if upper_limit < 0:
raise ValueError("Limit for the Catalan sequence must be ≥ 0" )
lowerCamelCase : Any = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
lowerCamelCase : Optiona... | 311 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class a__ ( unittest.TestCase ):
def ... | 507 | 0 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE ={
"""xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/config.json""",
"""x... | 89 |
import requests
def a (_lowerCAmelCase , _lowerCAmelCase ):
SCREAMING_SNAKE_CASE_ = {'''Content-Type''': '''application/json'''}
SCREAMING_SNAKE_CASE_ = requests.post(_lowerCAmelCase , json={'''text''': message_body} , headers=_lowerCAmelCase )
i... | 89 | 1 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase = BeautifulSoup(requests.get(__SCREAMING_SNAKE_CASE , params=__SCREAMING_SNAKE_CASE ).content , 'html.parser' )
lowercase = ... | 84 |
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the roo... | 383 | 0 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def __magic_name__ ( A : bool = True, *A : int, **A : List[Any] ):
'''simple docstring'''
if not is_tqdm_availabl... | 662 |
def __magic_name__ ( A : int, A : int, A : int ):
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
a = _modexpt(A, exponent // 2, A ) % modulo_value
return (x * x) % modulo_value
else... | 662 | 1 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase ( __snake_case : str , __snake_case : int , __snake_case : Union[str, Any] , __snake_case : str=5 ... | 231 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tenso... | 231 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 704 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowercase__ = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr... | 492 | 0 |
'''simple docstring'''
import math
import sys
def _A ( A ) -> Dict:
if number != int(a__ ):
raise ValueError("the value of input must be a natural number" )
if number < 0:
raise ValueError("the value of input must not be a negative number" )
if number == 0:
return ... | 372 |
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 : Optional[Any] = 10
def _UpperCAmelCase ( a__ , a__ , a__ , a__):
'''simple docstring'''
... | 540 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logg... | 351 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
... | 351 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ : List[str] = {'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG... | 115 |
'''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_sentencepi... | 207 | 0 |
'''simple docstring'''
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def __a(SCREAMING_SNAKE_CASE_ : Dict[str, torch.Tensor] ):
'''simple docstring'''
_lowerCAmelCase = []
... | 703 |
'''simple docstring'''
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import f... | 489 | 0 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowerCamelCase = numpy.array([0, 0])
lowerCamelCase = numpy.array([0.5, 0.8_660_254])
lowerCamelCase = numpy.array([1, 0... | 82 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 82 | 1 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
__lowerCAmelCase :List[str] = version.p... | 705 |
def A ( UpperCAmelCase ):
if n == 1 or not isinstance(UpperCAmelCase , UpperCAmelCase ):
return 0
elif n == 2:
return 1
else:
_snake_case : List[Any] = [0, 1]
for i in range(2 , n + 1 ):
... | 278 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Tuple = logging.get_logger(__name__)
_lowercase : Any = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class _Upp... | 641 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __snake_case ( UpperCamelCase_ ):
... | 171 | 0 |
import numpy as np
def a__ ( snake_case , snake_case ):
"""simple docstring"""
return np.where(vector > 0 , UpperCamelCase__ , (alpha * (np.exp(UpperCamelCase__ ) - 1)) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 720 |
import functools
def a__ ( snake_case , snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Tuple = len(snake_case )
__SCREAMING_SNAKE_CASE : Optional[int] = len(snake_case )
@functools.cache
def min_distance(snake_case , snake_case ... | 131 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Optional[Any] , a_ : int , a_ : MutableSequence[float] ):
"""simpl... | 69 |
'''simple docstring'''
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('''hub/hopper-medium-v2/unet/hor32''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/unet/hor128''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/value_function''', exist_ok=Tr... | 69 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.mo... | 480 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
... | 480 | 1 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[Any] = {
"google/umt5-small":... | 419 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from transformer... | 419 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_... | 720 |
'''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 PoolFormerConfig, PoolFormerForImageClassificatio... | 44 | 0 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( a_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict =(EulerDiscreteScheduler,)
SCREAMING_SN... | 282 |
'''simple docstring'''
import operator
def snake_case ( snake_case : list , snake_case : bool = False , snake_case : list | None = None ) -> list:
"""simple docstring"""
lowerCAmelCase = operator.lt if reverse else operator.gt
lowerCAmelCase =... | 284 | 0 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a = logging.get_logger(__name__)
a = {"vocab_file": "vocab.json"}
a = {
"vocab_file": {
"mgp-str"... | 721 |
def _SCREAMING_SNAKE_CASE ( snake_case , snake_case ) -> bool:
_UpperCAmelCase = len(snake_case ) + 1
_UpperCAmelCase = len(snake_case ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i o... | 175 | 0 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def _a ( _lowerCamelCase ) -> List[str]:
"""simple docstring"""
__snake_case : str ... | 26 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Tuple = ["image_processor", "tokenizer"]
_SCREAMING_SNAKE_CASE : Optional[int] = "CLIPImag... | 521 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
i... | 630 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase: Optional[int] = logging.get_logger(__name__)
class lowercase_ (lowercase__ ):
snake_case ='timm_backbone'
def __init__( self , lowercase_=None , lower... | 20 |
'''simple docstring'''
from __future__ import annotations
from random import random
class snake_case :
"""simple docstring"""
def __init__( self : Tuple , __A : int | None = None ):
__UpperCamelCase = value
__UpperCamelCase = random()
__UpperC... | 399 | 0 |
'''simple docstring'''
def _A ( A = 2_0_0 ) -> int:
lowercase : str = [1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
lowercase : List[str] = [0] * (pence + 1)
lowercase : Optional[int] = 1 # base case: 1 way to make 0 pence
for coin in coins:
for i in range(... | 720 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import DistilBertConfig, 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 ModelT... | 425 | 0 |
"""simple docstring"""
import numpy
# List of input, output pairs
SCREAMING_SNAKE_CASE__ : Optional[Any] =(
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
SCREAMING_SNAKE_CASE__ : str =(((515, 22, 13), 555), ((61, 35,... | 434 | """simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def UpperCamelCase ( SCREAMING_SNAKE_CASE_ ) ->Union[str, Any]:
return ConvertCommand(
args.model_type , args.tf_checkpoint ,... | 434 | 1 |
'''simple docstring'''
__magic_name__ : Any = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import Streaming... | 720 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configurat... | 602 | 0 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytessera... | 25 |
# 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... | 429 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timeste... | 720 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase : int = {
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 134 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def A ( __UpperCamelCase ) -> List[str]:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/... | 9 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCamelCase : Optional[Any] = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Data2VecAudioConfig"""],
"... | 80 | 0 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
SCREAMING_SNAKE_CASE = object()
# For specifying empty leaf dict `{}`
SCREAMING_SNAKE_CASE = ... | 711 | """simple docstring"""
def __lowerCAmelCase( __UpperCAmelCase ):
"""simple docstring"""
stooge(__UpperCAmelCase ,0 ,len(__UpperCAmelCase ) - 1 )
return arr
def __lowerCAmelCase( __UpperCAmelCase ,__UpperCAmelCase ,__UpperCAmelCase ):
"""simple docstring"... | 283 | 0 |
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... | 16 |
'''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 snake_case_ ( SCREAMING_SNAKE_CASE__ , S... | 672 | 0 |
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_params... | 706 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __A ( SCREAMING_SNAKE_CASE_ ):
UpperCAmelCase__ = "SpeechT5FeatureExtractor"
UpperCAmelCase__ = "SpeechT5Tokenizer"
def __init__( self : List[Any] , __sn... | 213 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 445 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : List[Any] = logging.get_logger(__name__)
snake_case : Dict = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 445 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase ... | 716 |
"""simple docstring"""
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 lowercase ( A_ )->... | 135 | 0 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__lowerCAmelCase : Tuple =HfArgumentParser(InitializationArguments)
__lowerCAmelCase : Tuple =pa... | 440 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__lowerCAmelCase : Optional[Any] ... | 440 | 1 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def lowerCamelCase_ ( _lowercase , _lowercase ) -> np.array:
__A : List[str] = F"{sampling_rate}"
__A : List[Any] = "1"
... | 387 | 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, prepare_image_inputs
... | 387 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : str = {
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 107 | '''simple docstring'''
import datasets
from .evaluate import evaluate
__SCREAMING_SNAKE_CASE : Optional[Any] = """\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
... | 244 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 205 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case_ : str ={
'''configuration_blip''': [
'''BLIP_PRETRAINED_CONFIG_ARCHIVE... | 205 | 1 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
UpperCAmelCase_ = logging.get_logger(__name__)
@da... | 271 | from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowerCAmelCase_ ( lowercase: str = "" ) -> dict[str, float]:
'''simple docstring'''
_UpperCamelCase: Tuple = url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
_UpperCame... | 271 | 1 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, loggi... | 714 |
'''simple docstring'''
def __lowerCamelCase ( SCREAMING_SNAKE_CASE_ : list[int] ) -> list[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = len(SCREAMING_SNAKE_CASE_ )
for i in range(SCREAMING_SNAKE_CASE_ ):
fo... | 68 | 0 |
"""simple docstring"""
def __magic_name__ ( lowercase , lowercase ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowercase , int(b / 2 ) ) * actual_power(lowercase , int(b / 2 ) )
else:
return a * actual_power(lowercase ... | 409 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : Optional[int] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
'came... | 587 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transforme... | 691 |
'''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 691 | 1 |
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
@require_tokenizers
class ... | 500 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_lowercase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def... | 5 | 0 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase ( __UpperCAmelCase ):
@require_torch
def SCREAMING_SNAKE_CAS... | 713 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_m... | 273 | 0 |
'''simple docstring'''
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must b... | 72 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def UpperCamelCase__ ( lowercase__ : str , lowercase__ : List[Any] , lowercase__ : int ):
snake_case : Tuple = 0
if start < end:
snake_case ... | 134 | 0 |
'''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 ..... | 720 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Au... | 211 | 0 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase__ ( __UpperCamelCase , unittest.TestCase ):
__UpperCAme... | 607 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
ge... | 607 | 1 |
from scipy.stats import spearmanr
import datasets
UpperCAmelCase__ : Optional[Any] = '\nThe Spearman rank-order correlation coefficient is a measure of the\nrelationship between two datasets. Like other correlation coefficients,\nthis one varies between -1 and +1 with 0 implying no correlation.\nPos... | 701 |
import baseaa
def _A ( _UpperCamelCase ):
return baseaa.baaencode(string.encode('''utf-8''' ) )
def _A ( _UpperCamelCase ):
return baseaa.baadecode(_UpperCamelCase ).decode('''utf-8''' )
if __name__ == "__main__":
UpperCAmelCase__ : Union[str, Any] = 'Hello World!'
... | 416 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_atten... | 11 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import B... | 515 | 0 |
'''simple docstring'''
# flake8: noqa
# Lint as: python3
_SCREAMING_SNAKE_CASE = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import Veri... | 56 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE ... | 56 | 1 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class UpperCamelCase_ ( unittest.TestCase , a_ ):
def UpperCamelCase_ ( self ) -> Any:
"""simple docstring"""
... | 673 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCase_ ( a_ )... | 673 | 1 |
"""simple docstring"""
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forwar... | 715 |
"""simple docstring"""
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
SCREAMING_SNAKE_CASE = ... | 556 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator... | 68 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _UpperCamelCase (*_lowerCamelCase : str , _lowerCamelCase : Optional[Union[Dict, Any]] = None , _lowerCamelCase : List[Any]=True , _low... | 24 | 0 |
'''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
... | 41 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,... | 41 | 1 |
from math import pi, sqrt, tan
def lowerCamelCase__ ( _a):
if side_length < 0:
raise ValueError("surface_area_cube() only accepts non-negative values")
return 6 * side_length**2
def lowerCamelCase__ ( _a , _a , _a):
if length < 0 or breadth < 0 or height < 0:
raise Value... | 25 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 477 | 0 |
from collections import namedtuple
lowerCAmelCase__ : Optional[Any] = namedtuple('''from_to''', '''from_ to''')
lowerCAmelCase__ : Optional[Any] = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.0_01, 10_00),
'''kilolitre''': from_to(1, 1),
'''gallon''': from_to(0... | 717 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase__ : List[str] = HfApi()
lowerCAmelCase__ : str = {}
# fmt: off
lowerCAmelCase__ : int = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, 0.63_47, 1.34_33, -1... | 699 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
SCREAMING_SNAKE_CASE_:List[Any] = logging.get_logger(__n... | 662 |
from typing import Any
import numpy as np
def __UpperCamelCase ( _lowerCAmelCase ) -> bool:
"""simple docstring"""
return np.array_equal(_lowerCAmelCase , matrix.conjugate().T )
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> ... | 662 | 1 |
import gc
import threading
import time
import psutil
import torch
class __snake_case :
def __init__( self ):
"""simple docstring"""
lowerCAmelCase__ = psutil.Process()
lowerCAmelCase__ = False
def SCREAMING_SNAKE_CASE_ ( self ):
... | 604 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class __snake_case ( SCREAMING_SNAKE_CASE ):
def __init__( self ,a_ ,a_ ):
"""simple docstring"""
lowerCAmelCase__ = params
lowerCAmelCase__ = n... | 604 | 1 |
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class a__ ( lowerCamelCase_ ):
def __init__( self : Optional[Any],_A : Tuple,_A : Tuple ):
"""simple docstring"""
super().__init__()
... | 216 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_ten... | 247 | 0 |
"""simple docstring"""
def lowercase ( ) -> int:
return 1
def lowercase ( __UpperCamelCase ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowercase ( __UpperCamelCase ) -> int:
return 0 if x < 0 else five_pence(x - 5 )... | 705 |
"""simple docstring"""
from collections.abc import Sequence
from queue import Queue
class _lowercase :
def __init__( self , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_=None , UpperCamelCase_=None ):
__magic_name__ = ... | 190 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase__ : Dict = {
'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.j... | 98 |
"""simple docstring"""
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_t... | 58 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple reposito... | 704 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils ... | 325 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( a__ , a__ , a__) -> float:
"""simple docstring"""
return round(float(moles / volume) * nfactor)
def lowerCamelCase__ ( a__ , a__ , a__) -> float:
"""simple docstring"""
return ... | 517 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
SCREAMING_SNAKE_CASE_ = {
"albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/config.json",
"albert-large-v1": "h... | 517 | 1 |
"""simple docstring"""
# Imports
import numpy as np
class a__ :
def __init__( self : Optional[int] , UpperCamelCase_ : Tuple=None , UpperCamelCase_ : List[str]=None , UpperCamelCase_ : str=None , UpperCamelCase_ : List[str]=N... | 487 |
"""simple docstring"""
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase = False ) -> bool:
"""simple docstring"""
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n % 10 not in (1, 3, 7, 9): # can quickly check last digit
... | 487 | 1 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(_lowercase ) , '''Tatoeba directory doe... | 194 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _int... | 194 | 1 |
def __lowerCAmelCase ( snake_case : int = 10**12 ) -> int:
__lowerCamelCase: str = 1
__lowerCamelCase: List[Any] = 0
__lowerCamelCase: Any = 1
__lowerCamelCase: Optional[Any] = 1
while numerator <= 2 * min_total - 1:
prev_numerator += 2... | 702 |
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
_A : ... | 189 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/m... | 5 |
__lowerCamelCase : Optional[Any] = {
"""A""": """.-""", """B""": """-...""", """C""": """-.-.""", """D""": """-..""", """E""": """.""", """F""": """..-.""", """G""": """--.""",
"""H""": """....""", """I""": """..""", """J""": """.---""", """K""": """-.-""", """L""": """.-..""", """M""": ""... | 385 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelera... | 706 | from __future__ import annotations
def a__ ( __UpperCamelCase ):
SCREAMING_SNAKE_CASE_ = str(__UpperCamelCase )
return n == n[::-1]
def a__ ( __UpperCamelCase = 1_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ = 0
for i in range(1 , __UpperCamelCase ... | 356 | 0 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin, SchedulerOutput
@d... | 404 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCAmelCase__ = TypeVar('''T''')
class __snake_case ( Generic[T]):
def __init__( self : int , __lowerCAmelCase : T ):
... | 83 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase__ ( UpperCAmelCase , UpperCAmelCase = None , UpperCAmelCase = None , UpperCAmelCase = False , ):
"""simple docstring"""
snake_case__ : Tupl... | 705 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowerCAmelCase__ ( UpperCAmelCase ):
"""simple docstring"""
snake_case__ : List[str] = year % 19
snake_case__ : Optional[Any] = ye... | 172 | 0 |
from __future__ import annotations
import time
import numpy as np
UpperCamelCase = [8, 5, 9, 7]
UpperCamelCase = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
UpperCamelCase = [
[3, 2, 1, 4],
[0, 2, 5, 2... | 520 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( UpperCAmelCase__ ):
"""simple docstring"""
if len(UpperCAmelCase__ ) == 0:
return array
_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = min(UpperCAmelCase__ ), max(UpperCAmelCase__ ... | 605 | 0 |
"""simple docstring"""
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('socket.socket' )
@patch('builtins.open' )
def _snake_case ( lowercase__ , lowercase__ ):
# ===== initialization =====
_lowerCamelCa... | 492 |
"""simple docstring"""
def _snake_case ( lowercase__ = 1000 ):
_lowerCamelCase, _lowerCamelCase : Optional[int] = 1, 1
_lowerCamelCase : int = []
for i in range(1 , n + 1 ):
_lowerCamelCase : Tuple = prev_numerato... | 492 | 1 |
from __future__ import annotations
def A ( __UpperCamelCase , __UpperCamelCase ) -> list[int]:
A__ = 0
A__ = len(__UpperCamelCase ) - 1
while i < j:
if nums[i] + nums[j] == target:
return [i, j]
elif nums[i] + nums[j] < target:
A... | 9 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( lowercase ):
"""simple docstring"""
def __init_... | 645 | 0 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import... | 557 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class SCREAMING_SNAKE_CASE_ ( _a ):
"""simp... | 557 | 1 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_a: Dict = logging.get_logger(__name__)
class __UpperCamelCase ( lowercase ):
def __init__( self : str , *lowerCAmelCase : Dict , **lowerCAmelCas... | 162 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
snake_case = {"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMAEConf... | 67 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def UpperCAmelCase__ ( UpperCAmelCase__, UpperCAmelCase__, UpperCAmelCase__, UpperCAmelCase__, Up... | 716 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A__ ( _snake_case ):
lowercase = "ClapFeatureExtractor"
lowercase = ("RobertaTokenizer", "RobertaTokenizerFast")
def __init__( self ... | 667 | 0 |
'''simple docstring'''
import sys
UpperCAmelCase_ : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''1254069874715852386305071569329096329522744304355... | 24 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_lowerCamelCase : List[Any] = logging.getLogger(__name__)
class snake_case__ ( __snake_case ):
... | 121 | 0 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowercase : List[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
impor... | 397 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
_lowercase : Tuple = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config... | 397 | 1 |
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
lowercase : Dict = WebClient(token=os.environ["CI_SLACK_BOT_TOKEN"])
def snake_case__ ( lo... | 542 |
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_availab... | 542 | 1 |
"""simple docstring"""
def _snake_case ( lowercase__ ):
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
_lowerCamelCase : Optional[Any] = sum(lowercase__ ) / len(lowercase__ ) # Calculate the average
return... | 492 |
"""simple docstring"""
def _snake_case ( lowercase__ ):
_lowerCamelCase : Optional[int] = int(lowercase__ )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowercase__ )
_lowerCamelCase, _lowerCamelCase : Dict = divmod... | 492 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__a: Tuple = logging.get_logger(__name__)
__a: List[Any] = {
'''facebook/convnextv2-tiny-1k-224... | 108 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
A__ : Any = {'UserAgent': UserAgent().random}
def _snake_case ( lowerCamelCase__ : Optional[Any] ) -> ... | 153 | 0 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def A__ ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with pytest.raises(snake_case_ ... | 107 | import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _lowerCamelCase ( unittest.TestCase ):
def UpperCamelCase_ ( self ) -> str:
SCREAMING_SNAKE_CASE__: List[Any]= [
'''safety_checker/pytorch_model.bin''',
'... | 107 | 1 |
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