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 |
|---|---|---|---|---|
import re
def __UpperCamelCase ( _lowerCAmelCase ):
"""simple docstring"""
if len(re.findall("[ATCG]" , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError("Invalid Strand" )
return dna.translate(dna.maketrans("ATCG" , "TAGC" ) )
if __name__ == "__main... | 333 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase =logging.get_logger(__name__)
__lowerCAmelCase ={
"huggingface/informer-tourism-monthly": (
"https://huggingface.co/huggingface/informer-tourism-mon... | 333 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( __a ):
"""simple docstring"""
__magic_name__ = (PNDMScheduler,)
__magic_name_... | 700 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 0 |
import os
import time
import numpy as np
import onnxruntime as ort
lowerCamelCase__ : int = '1'
lowerCamelCase__ : Optional[int] = '0'
lowerCamelCase__ : Optional[Any] = '1'
lowerCamelCase__ : int = ort.SessionOptions()
lowerCamelC... | 31 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : int = 10**9):
A_ : Optional[int] = 1
A_ : int = 2
A_ : List[Any] = 0
A_ : Optional[Any] = 0
A_ : str = 0
while perimeter <= max_perimet... | 665 | 0 |
def UpperCamelCase_ ( __SCREAMING_SNAKE_CASE, __SCREAMING_SNAKE_CASE, __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
snake_case_ : Union[str, Any] = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total... | 701 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
f... | 92 | 0 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
... | 109 |
lowerCAmelCase_ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def __lowerCAmelCase ( UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase ) ... | 678 | 0 |
'''simple docstring'''
def __a(SCREAMING_SNAKE_CASE_ : int = 4000000 ):
'''simple docstring'''
_lowerCAmelCase = [0, 1]
_lowerCAmelCase = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
... | 716 |
'''simple docstring'''
import math
def __a(SCREAMING_SNAKE_CASE_ : int = 100 ):
'''simple docstring'''
_lowerCAmelCase = sum(i * i for i in range(1 , n + 1 ) )
_lowerCAmelCase = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
... | 489 | 0 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int, __snake_case : int ) -> int:
"""simple docstring"""
return abs(UpperCAmelCase__ ) if a == 0 else greatest_common_divisor(b % a, UpperCAmelCase__ )
def __lowerCamelCase ( __snake_case : ... | 215 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase = {
'''<''': operator.lt,
'''<=''': operator.le,
'''==''': operator.eq,
'''!=''': operator.ne,
'''>=''': operator.ge,
'''>''': operator.gt,
}
... | 272 | 0 |
def UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) -> str:
'''simple docstring'''
_A= ''
for word_or_phrase in separated:
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise Excepti... | 476 | from jiwer import compute_measures
import datasets
UpperCAmelCase_ = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved evaluation measures ... | 476 | 1 |
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
UpperCamelCase = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang, Alex and Singh, Ama... | 66 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase = {
"configuration_gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig", "GPTNeoOnnxConfig"],
}
try:
if not is_torch_availab... | 66 | 1 |
from PIL import Image
def A_ ( __a : Image ):
"""simple docstring"""
a__ , a__ = image.size
a__ = 0
a__ = image.load()
for i in range(__a ):
for j in range(__a ):
a__ = pixels[j, i]
... | 351 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __snake_case ( SCREAMING_SNAKE_CASE ,SCREA... | 351 | 1 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __lowercase ( __lower... | 335 |
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
snake_case : str = '''\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang, Alex and Singh, Aman... | 335 | 1 |
'''simple docstring'''
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from... | 718 |
'''simple docstring'''
def lowercase ( lowerCAmelCase : int = 100_0000):
"""simple docstring"""
_A : Any = 1
_A : str = 1
_A : Dict = {1: 1}
for inputa in range(2 , lowerCAmelCase):
_A : Any = 0
... | 417 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
_lowerCamelCase = """
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed ... | 71 |
'''simple docstring'''
import math
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 SchedulerMixin, SchedulerOutput
class lowerCamelCase ( lowercase_ , lowercase_ ):
... | 215 | 0 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__a = TypeVar("KEY")
__a = TypeVar("VAL")
@dataclass(frozen=UpperCamelCase_ , slots=UpperCamelCase_ )
class lowerCamelC... | 703 |
"""simple docstring"""
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
__a = logging.get_logger(__name__)
class lowerCamelCase :
'''simple docstring'''
_A : Union[str, Any] = None... | 310 | 0 |
'''simple docstring'''
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 301 |
'''simple docstring'''
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__) # pylint: disab... | 301 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'''
)... | 719 | import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from ...utils impo... | 387 | 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_image_inputs
if is_torch_availa... | 48 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def A ( UpperCamelCase_ : List[Any] , UpperCamelCase_ : int , UpperCamelCase_ : List[Any] ) -> Dict:
'''simple docstring'''
lowerCAmelC... | 48 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenizati... | 709 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
'facebook/s2t-small-librispeech-asr': (
'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json'
... | 217 | 0 |
from manim import *
class lowercase ( A__ ):
'''simple docstring'''
def snake_case_ ( self ) -> Union[str, Any]:
"""simple docstring"""
UpperCAmelCase = Rectangle(height=0.5 , width=0.5 )
... | 254 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
"facebook/encodec_24khz": "https://huggingface.co/facebook/encodec_24khz/res... | 254 | 1 |
"""simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_wa... | 705 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team and The OpenBMB 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.a... | 397 | 0 |
from __future__ import annotations
import numpy as np
def _lowerCAmelCase ( _lowerCAmelCase ) -> int:
'''simple docstring'''
return np.maximum(0 , _lowerCAmelCase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) #... | 371 |
import requests
from bsa import BeautifulSoup
def _lowerCAmelCase ( _lowerCAmelCase = "AAPL" ) -> str:
'''simple docstring'''
__snake_case = F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
__snake_case = BeautifulSoup... | 371 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop,... | 716 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowercase ( _SCREAMING_SNAKE_... | 95 | 0 |
from __future__ import annotations
def _lowerCAmelCase ( UpperCamelCase__: list[int] ) -> list[int]:
"""simple docstring"""
if len(UpperCamelCase__ ) == 0:
return array
A , A = min(UpperCamelCase__ ), max(UpperCamelCase__ )
# Compute the variabl... | 641 |
import numpy as np
from transformers import Pipeline
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optional[int]:
"""simple docstring"""
A = np.max(UpperCamelCase__ , axis=-1 , keepdims=UpperCamelCase__ )
A = np.exp(out... | 641 | 1 |
"""simple docstring"""
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class lowerCamelCase__ :
def __init__( self : str , Upp... | 708 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase ( _UpperCamelCase : int ) -> list[int]:
'''simple docstring'''
__UpperCAmelCase : Tuple = 2
__UpperCAmelCase : Optional[Any] = []
while i * i <= n:
... | 299 | 0 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
__SCREA... | 236 |
'''simple docstring'''
from manim import *
class A_ ( lowerCAmelCase_ ):
def lowercase ( self : Dict ):
_UpperCAmelCase = Rectangle(height=0.5 , width=0.5 )
_UpperCAmelCase = Rectangle(height=0.4_6 , width=0.4_6 ... | 236 | 1 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
A ={
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
'self.proj': '... | 710 |
'''simple docstring'''
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
... | 358 | 0 |
from __future__ import annotations
def a__ ( lowercase__ , lowercase__ , lowercase__ , ):
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("You cannot supply more or less than 2 valu... | 54 |
from __future__ import annotations
def a__ ( lowercase__ , lowercase__ ):
'''simple docstring'''
if len(lowercase__ ) == 0:
return False
UpperCAmelCase_ =len(lowercase__ ) // 2
if a_list[midpoint] == item:
return True
... | 54 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : int = {
"""configuration_upernet""": ["""UperNetConfig"""],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Opt... | 584 | import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a__ ( __SCREAMING_SNAKE_CASE ):
_A = ["image_processor", "tokenizer"]
_A = "CLIPImageProcessor"
_A = ("CLIPTokeni... | 584 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
BertToken... | 197 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 197 | 1 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import Bat... | 706 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase_ = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'''],
}
try:
if not is_torch_ava... | 322 | 0 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transform... | 62 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
"""Jukeb... | 62 | 1 |
"""simple docstring"""
def lowercase__(A ) ->bool:
lowercase__ : Tuple= (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowercase__(A = 5_000 ) ->int:
lowercase__ : str= [(i * (3 * i - 1)) // 2 for i in range(1 ... | 715 |
"""simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase__(A ) ->bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
e... | 85 | 0 |
def _UpperCAmelCase (UpperCamelCase_ : int = 100 ):
'''simple docstring'''
_lowerCAmelCase : Any = (n * (n + 1) // 2) ** 2
_lowerCAmelCase : Tuple = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":... | 429 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=_a )
class __snake_case (_a ):
lowerCAmelCase__ = field(default="audio-classification" , metad... | 429 | 1 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import r... | 707 |
'''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _lowerCAmelCase ( __magic_name__ : Dict ) -> Dict:
for param in module.parameters():
lowercase : List[str] =False
def _lowerCAmelCase... | 88 | 0 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
_snake_case = str(bin(_SCREAMING_SNAKE_CASE ) )[2:] # remove the leading "0b"
_s... | 585 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
class lowercase_ ( a_ ):
def __init__( self : int , _lowercase : List[str]=None , **_lowerca... | 308 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,... | 705 |
_UpperCamelCase : Optional[int] = 8.31_44_62 # Unit - J mol-1 K-1
def __UpperCamelCase ( snake_case , snake_case , snake_case ) -> float:
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter... | 341 | 0 |
def _lowerCamelCase ( snake_case , snake_case ):
assert x is not None
assert y is not None
_lowerCAmelCase = len(snake_case )
_lowerCAmelCase = len(snake_case )
# declaring the array for storing the dp values
_lowerCAmelCase = [[0]... | 192 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Optional[int] = x
UpperCamelCase : str = ... | 102 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
loggin... | 713 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
lowerCAmelCase__: List[Any] = logging.get_logger(__name__)
class snake_case_ :
__lowerCamelCase : Any = None
@experimental
def ... | 311 | 0 |
"""simple docstring"""
from __future__ import annotations
import typing
from collections import Counter
def _A( lowerCAmelCase ):
A__ : typing.Counter[int] = Counter()
for base in range(1 , max_perimeter + 1 ):
for perpendicular in range(UpperCamelCas... | 363 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class UpperCAmelCase ( _snake_case ... | 467 | 0 |
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""",
""... | 552 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
c... | 552 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = 0
if start < end:
lowerCAmelCase__ = randint(lowercase_ , lowercase_ )
low... | 615 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class _a (unittest.TestCase , __magic_nam... | 456 | 0 |
"""simple docstring"""
import pprint
import requests
SCREAMING_SNAKE_CASE_ = 'https://zenquotes.io/api'
def lowercase ():
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ():
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
if ... | 712 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class lowerCAmelCase_ ( A__ ):
'''simple docstring'''
def A__ ( self , snake_case_ ) -> Optional[int]:
... | 573 | 0 |
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
__magic_name__ : Tuple = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
def __init__( self : List[str] , *__lo... | 615 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 1 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
__UpperCAm... | 98 |
'''simple docstring'''
from math import pi, sqrt, tan
def _snake_case ( A ) -> float:
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''' )
return 6 * side_length**2
def _snake_case ( A ... | 98 | 1 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class a_ ( lowercase__ ):
def __init__( self , SCREAMING_SNAKE_CASE="" , SCREAMING_SNAKE_CASE="train" ) -> Any:
"""simple docstring"""
assert os.p... | 205 |
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 579 | 0 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (... | 707 |
'''simple docstring'''
from PIL import Image
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
SCREAMING_SNAKE_CASE_ :List[Any] = (259 * (level + 255)) / (255 * (259 - level))
def contrast(SCREAMING_SNAKE_CASE ) -> int:
return int(128 + f... | 233 | 0 |
'''simple docstring'''
import unittest
from knapsack import knapsack as k
class a__ ( unittest.TestCase ):
'''simple docstring'''
def lowerCAmelCase ( self : Optional[Any] ) -> Optional[Any]:
__A= 0
__A= [0]
__A= [0]
__A= len(lowerCAme... | 186 |
'''simple docstring'''
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git w... | 186 | 1 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _SCREAMING_SNAKE_CASE ( _lowerCAmelCase ):
a_ : Union[str, Any] = ''''''
a_ : Dict = (
None # protocol passed i... | 703 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def SCREAMING_SNAKE_CASE ( ... | 142 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
... | 11 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowercase : Tuple = (DDPMScheduler,)
def _lowercase... | 5 | 0 |
'''simple docstring'''
from collections.abc import Sequence
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase = False ) -> float:
'''simple docstring'''
if not arr:
return 0
__SCREAMING_SNAKE_CASE = 0 if allow_empty_subarrays... | 701 |
'''simple docstring'''
import sys
from collections import defaultdict
class __a :
def __init__( self : Dict ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
def UpperCAmelCase__ ( self : List[Any] ,lowerCamelCase : ... | 13 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, BlipImagePro... | 201 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCAmelCase = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowerConfig',
'BridgeTowerTextCo... | 201 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_... | 710 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
A = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_copies # noqa: E402
# This is ... | 487 | 0 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.mode... | 103 |
"""simple docstring"""
from copy import deepcopy
class UpperCAmelCase :
def __init__( self : Optional[Any] , __lowerCamelCase : list[int] | None = None , __lowerCamelCase : int | None = None ):
"""simple docstring"""
... | 103 | 1 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
re... | 247 |
from ..utils import DummyObject, requires_backends
class A (metaclass=SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__lowerCamelCase : Any = ['''keras_nlp''']
def __init__( self : Any , *__lowerCAmelCase : Any ... | 247 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
class UpperCamelCase__ ( lowerCamelCase__ ):
'''simple docstring'''
__a : Tuple = """e... | 458 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"""google/canine-s""": """https://huggingface.co/google/canine-s/resolve/main/config.json""",
# See all CANINE models at ht... | 458 | 1 |
_lowerCamelCase : Any = 256
# Modulus to hash a string
_lowerCamelCase : Dict = 1_000_003
def __a ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
SCREAMING_SNAKE_CASE : int = len(__lowerCAmelCase )
SCREAMING_SNAKE_CASE ... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : Optional[int] = logging.get_logger(__name__)
_lowerCamelCase : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json"... | 308 | 0 |
"""simple docstring"""
from __future__ import annotations
lowerCAmelCase_ : Optional[int] = list[list[int]]
# assigning initial values to the grid
lowerCAmelCase_ : Matrix = [
[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... | 673 |
"""simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLIComman... | 673 | 1 |
__UpperCamelCase : Optional[Any] = 256
# Modulus to hash a string
__UpperCamelCase : Any = 1000003
def _UpperCAmelCase ( UpperCAmelCase : str , UpperCAmelCase : str ):
"""simple docstring"""
__lowerCamelCase... | 458 |
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils import... | 458 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
__magic_name__: List[Any] = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}
__mag... | 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 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ ) -> str | Literal[False]:
'''simple docstring'''
__lowerCAmelCase = list(UpperCamelCase__ )
__l... | 719 |
from __future__ import annotations
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ ) -> list[str]:
'''simple docstring'''
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
ra... | 334 | 0 |
'''simple docstring'''
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 667 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : Union[str, Any] = int(np.ceil((x_end - xa) / step_s... | 667 | 1 |
class _lowerCAmelCase :
'''simple docstring'''
def __init__( self : Tuple ):
'''simple docstring'''
_snake_case : dict[str, TrieNode] = {} # Mapping from char to TrieNode
_snake_case : List[Any] = False
def... | 714 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c... | 669 | 0 |
import math
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> float:
"""simple docstring"""
if initial_intensity < 0:
raise ValueError("""The value of intensity cannot be negative""" )
# handling of negative values of initial intensity
... | 662 |
"""simple docstring"""
from __future__ import annotations
UpperCamelCase : Any = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __snake_case ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ... | 690 | 0 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transforme... | 709 |
import cva
import numpy as np
class UpperCamelCase__ :
def __init__( self : List[str] , UpperCamelCase__ : float , UpperCamelCase__ : int ):
'''simple docstring'''
if k in (0.04, 0.06):
lowercas... | 650 | 0 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _UpperCamelCase ( lowerCAmelCase_ = 3 ) ->qiskit.result.counts.Counts:
if isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise TypeError("""number of... | 377 |
from __future__ import annotations
import math
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not pr... | 377 | 1 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data ... | 645 | """simple docstring"""
import argparse
import gc
import json
import os
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 ac... | 645 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase ={
"con... | 617 |
"""simple docstring"""
import qiskit
def _A ( _a : int , _a : int ):
"""simple docstring"""
A = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
A = qiskit.QuantumCircu... | 617 | 1 |
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,
generate_identified_filename,
infer_sh... | 81 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
... | 81 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import _LazyModule
SCREAMING_SNAKE_CASE_ = {"tokenization_tapex": ["TapexTokenizer"]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
SCREAMING_SNAKE_CASE_ ... | 597 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta imp... | 507 | 0 |
def _lowerCAmelCase (_lowerCAmelCase):
if not isinstance(_lowerCAmelCase , _lowerCAmelCase):
raise ValueError("Input must be an integer")
if input_num <= 0:
raise ValueError("Input must be positive")
return sum(
divisor for divisor in range(1 , input_num // 2 + ... | 504 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
UpperCAmelCase : Optional[Any] =pytest.mark.integration
@pytest.mark.parametrize("path" , [... | 504 | 1 |
import requests
from bsa import BeautifulSoup
def snake_case_ ( lowerCAmelCase_ : str = "AAPL" ):
__lowercase : List[Any] = F"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
__lowercase : List[Any] = BeautifulSoup(requests.get(lowerCAmelCase... | 149 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : List[str] = {
'''configuration_conditional_detr''': [
'''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Condition... | 149 | 1 |
UpperCamelCase__ = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def _UpperCamelCase ():
"""simple docstring"""
UpperCamelCase__ = input("""Enter message: """ )
UpperCamelCase__ = input("""Enter key [alphanumeric]: """ )
UpperCamelCase__... | 548 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json",
# Se... | 548 | 1 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
__UpperCamelCase: List[Any] = TypeVar("""T""")
class __lowerCAmelCase ( Generic[T] ):
'''simple docstring'''
_A = 42 # Cache sto... | 266 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def SCREAMING_SNAKE_CASE__ ( _lowercase : dict ) ->... | 266 | 1 |
def __SCREAMING_SNAKE_CASE ( __UpperCamelCase : int ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = [1]
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = 0, 0, 0
SCREAMING_SNAKE_C... | 379 | import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features ... | 379 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : List[str] = logging.get_logger(__name__)
UpperCamelCase : Optional[int] = {
'facebook/s2t-small-librispeech-asr': (
'https://huggingface.co/face... | 50 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 75 | 0 |
from math import isclose, sqrt
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> tuple[float, float, float]:
snake_case__ = point_y / 4 / point_x
snake_case__ = 2 * normal_gradient / (1 + normal_g... | 208 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 208 | 1 |
def _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
print('''\nThe shortest path matrix using Floyd Warshall algorithm\n''' )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(SCREAMING_SNAKE_CASE ):
if dist[i][j] != float('''inf''' )... | 43 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = 'T5Config'
class _a ( UpperCamelCase__ ):
_l... | 43 | 1 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
_lowercase = logging.get_logger(__name__)
class lowerCamelCase__ ( A__ ):
def __init__( self : List[str] , *__a : int , **__a : Dict ... | 242 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_bac... | 242 | 1 |
'''simple docstring'''
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import... | 207 |
'''simple docstring'''
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCAmelCase ( snake_case_ ):
def __init__( self :... | 207 | 1 |
'''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class __magic_name__ ( __SCREAMING_SNAKE_CASE ):
UpperCamelCase__ = 'EncodecFeatureExtractor'
UpperCamelCase__ = ('T5Tokenizer', 'T5... | 145 |
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
_UpperCAmelCase : List[str] = logging.get_logger(__name__)
def UpperCamelCase ( lowercase_ : O... | 145 | 1 |
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoModelForMaskedL... | 73 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIF... | 73 | 1 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case : Any = "1"
__snake_case : int = "0"
__snake_case : Any = "1"
__snake_case : List[str] = ort.SessionOptions()
__snake_case : Union[str, ... | 720 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json",
"microsoft/markuplm-large... | 181 | 0 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
__UpperCamelCase = logging.get_logger(__name__)
def UpperCamelCase_( _A :Tuple , _A :str , _... | 551 |
from __future__ import annotations
import math
import random
from typing import Any
class lowerCamelCase__ :
"""simple docstring"""
def __init__( self ):
'''simple docstring'''
UpperCamelCase__ = []
UpperCamelCase__ = 0
Uppe... | 551 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFXLMRobertaMod... | 713 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ : Optional[Any] = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mask2FormerConfig',
],
}
try:
... | 148 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
_a = 1.054571817E-34 # unit of ℏ : J * s
_a = 3E8 # unit of c : m * s^-1
def lowerCamel... | 19 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 658 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__A =logging.get_logger(__name__)
__A ={
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json"""
),
}
class _SCREAMING_S... | 700 |
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 =logging.get_logger(__name__)
__A ={
'''google/vit-base-patch16-224''': '''https://huggin... | 313 | 0 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging... | 628 |
"""simple docstring"""
from collections.abc import Sequence
def _SCREAMING_SNAKE_CASE ( UpperCamelCase : Sequence[int] | None = None ):
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
A__ = nums... | 574 | 0 |
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from t... | 700 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase__ = logging.get_logger(__name__)
class __lowercase ( a__ ):
def __init__( self : List[Any] , *lowercase__ : ... | 143 | 0 |
'''simple docstring'''
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_... | 577 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate... | 577 | 1 |
'''simple docstring'''
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_wei... | 603 | '''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__snake_case = logging.get_logger(__name__)
... | 603 | 1 |
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
__A =[
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
'''text-classification''',
'''language-model... | 463 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
__A =logging.getLogger(__name__)
def lowerCamelCase_ ( ):
lowerCamelCase_ = argparse.ArgumentParser(
description="Prepare TFRecord shards from pr... | 463 | 1 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_GENERA... | 717 | 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 direc... | 638 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class UpperCAmelCase ( A__ ... | 251 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
... | 73 | 0 |
'''simple docstring'''
def _a (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
assert (
isinstance(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) and number_of_steps > 0
), f'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
if number_of_st... | 271 |
'''simple docstring'''
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorSt... | 271 | 1 |
'''simple docstring'''
def UpperCamelCase_ ( snake_case_ : int=2_81_23 ) -> Tuple:
'''simple docstring'''
__lowerCAmelCase = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1 ):
sum_... | 427 | '''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( snake_case_ : list[int | float] , snake_case_ : int , snake_case_ : int ) -> int | float:
'''simple docstring'''
if len(snake_case_ ) == 0:
raise ValueError("""find_max() ... | 427 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCAmelCase = {
'configuration_chinese_clip': [
'CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ChineseCLIPConfi... | 708 |
'''simple docstring'''
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def __a ( self ,__SCREAMING_S... | 220 | 0 |
from collections import defaultdict
from math import ceil, sqrt
def A ( lowercase__ : int = 100_0000 , lowercase__ : int = 10 ) -> int:
UpperCamelCase__ :defaultdict = defaultdict(lowercase__ )
for outer_width in range(3 , (t_limit // 4) + 2 ):
if outer_width * outer_width >... | 45 |
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
snake_case__ = logging.get_logger(__name__)
def lowerCamelCase__ ... | 395 | 0 |
from typing import Any
import numpy as np
def A_ ( snake_case : np.ndarray ) -> bool:
'''simple docstring'''
return np.array_equal(snake_case , matrix.conjugate().T )
def A_ ( snake_case : np.ndarray , snake_case : np.ndarray ) -> ... | 451 |
def A_ ( snake_case : float ) -> float:
'''simple docstring'''
if edge <= 0 or not isinstance(snake_case , snake_case ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def A_ ( s... | 451 | 1 |
from timeit import timeit
lowerCamelCase__ = {
'''MALAYALAM''': True,
'''String''': False,
'''rotor''': True,
'''level''': True,
'''A''': True,
'''BB''': True,
'''ABC''': False,
'''amanaplanacanalpanama''': True, # "a man a plan a canal panama"
}
# Ensure our test data is valid
as... | 547 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logg... | 115 | 0 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def a__ ( _SCREAMING_SNAKE_CASE : Optional[int] , _SCREAMING_SNAKE_CASE : int=1 ) -> Tuple:
"""simple docstring""... | 710 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def a__ ( _SCREAMING_SNAKE_CASE : list ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
UpperCAmelCase_ : Tuple = {"+", "-", "*", "/"}
... | 323 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.