code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import struct
import unittest
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : Union[str, Any] , UpperCAmelCase : bytes ) -> None:
'''simple docstring'''
lowercase : Union[str, Any] ... | 717 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 0 |
'''simple docstring'''
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(... | 718 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : list ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
lowercase : Optional[Any] =[]
def generate(__A : int , __A : list ):
lowercase : ... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 0 |
'''simple docstring'''
from math import isqrt, loga
def lowercase_ ( __A : int ) -> list[int]:
"""simple docstring"""
lowercase : Dict =[True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i... | 720 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 0 |
'''simple docstring'''
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.configura... | 721 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimens... | 700 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 0 |
'''simple docstring'''
import unittest
from transformers import SqueezeBertConfig, 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 ... | 702 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 0 |
'''simple docstring'''
import math
def lowercase_ ( __A : list , __A : int ) -> int:
"""simple docstring"""
lowercase : Dict =len(__lowercase )
lowercase : List[str] =int(math.floor(math.sqrt(__lowercase ) ) )
lowercase ... | 703 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class UpperCAmelCase_ ( __lowercase ):
"""simple docstring"""
def __init__( self : List[Any] ... | 704 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__na... | 705 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
SCREAMING_SNAKE_CASE = '\\n\n'
SCREAMING_SNAKE_CASE = '\nPerplexity (PPL) is one of the most comm... | 706 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 0 |
'''simple docstring'''
import torch
from diffusers import StableDiffusionPipeline
SCREAMING_SNAKE_CASE = 'path-to-your-trained-model'
SCREAMING_SNAKE_CASE = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('cuda')
SCREAMING_SNAKE_CASE = 'A photo of sks dog in ... | 707 |
'''simple docstring'''
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 UpperCAmelCase_ ( ... | 8 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class UpperCAmelCase_ ( lowerCAmelCase__ ):
"""simple docstring"""
def __init__( self : int ... | 708 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 0 |
'''simple docstring'''
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
f... | 709 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE = {'''configuration_mmbt''': ['''MMBTConfig''']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependenc... | 710 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoToke... | 711 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', ... | 712 |
'''simple docstring'''
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 Padd... | 8 | 0 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class UpperCAmelCase_ ( __lo... | 713 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 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:
import torch
class Uppe... | 714 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 0 |
'''simple docstring'''
from manim import *
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
def A__ ( self : Optional[Any] ) -> Any:
'''simple docstring'''
lowercase : List[Any] =Rectangle(height=0.5 , width=0.5 )
l... | 715 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 0 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class UpperCAmelCase_ ( __lowerCAmelCase ):
"""simple docstrin... | 716 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : str , __A : Dict ) -> int:
"""simple docstring"""
return number | (1 << position)
def lowercase_ ( __A : Union[str, Any] , __A : List[Any] ) -> int:
"""sim... | 717 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 0 |
'''simple docstring'''
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_... | 718 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_availabl... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : str ) -> List[str]:
"""simple docstring"""
return "".join(chr(ord(__A ) - 3_2 ) if '''a''' <= char <= '''z''' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod(... | 720 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_longt5': ['LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LongT5Config', 'LongT5OnnxConfig'],
}
try:
... | 721 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 0 |
'''simple docstring'''
import torch
from diffusers import StableDiffusionPipeline
SCREAMING_SNAKE_CASE = 'path-to-your-trained-model'
SCREAMING_SNAKE_CASE = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('cuda')
SCREAMING_SNAKE_CASE = 'A photo of sks dog in ... | 700 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 0 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accel... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : int = 1_0 ) -> str:
"""simple docstring"""
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or n < 0:
raise ValueError('''Invalid input''' )
lowercase : Tuple =1_0**n
lowercase : Dic... | 702 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowercase_ ( __A : Tuple ) -> Union[str, Any]:
"""simple docstring"""
if (
(cp >= 0X4_e00 and cp <= 0X9_fff)
or (cp >= 0... | 703 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 0 |
'''simple docstring'''
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()... | 704 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_model... | 705 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
i... | 706 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 0 |
'''simple docstring'''
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRob... | 707 |
'''simple docstring'''
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 UpperCAmelCase_ ( ... | 8 | 0 |
'''simple docstring'''
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class UpperCAmelCase_ ( __A ):
"""simple ... | 708 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE... | 709 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 0 |
from itertools import count
def lowercase_ ( __A : int = 5_0 ) -> Optional[int]:
"""simple docstring"""
lowercase : Optional[Any] =[1] * min_block_length
for n in count(__A ):
fill_count_functions.append(1 )
for block_length in range(__A , ... | 710 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 711 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenizatio... | 712 |
'''simple docstring'''
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 Padd... | 8 | 0 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', 'U... | 713 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> int:
"""simple docstring"""
return 1 if input_a == input_a else 0
def lowercase_ ( ) -> None:
"""simple docstring"""
assert xnor_gate(0 , 0 )... | 714 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowercase_ ( __A : int | str ) -> bool:
"""simple docstring"""
lowercase : Optional[Any] =str(_UpperCamelCase )
return n == n[::-1]
def lowercase_ ( __A : int = 1_0_0_0_0... | 715 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 0 |
'''simple docstring'''
from math import pow
def lowercase_ ( __A : Any , __A : Dict , __A : Optional[Any] , __A : int , __A : Any , ) -> Optional[int]:
"""simple docstring"""
if current_sum == needed_... | 716 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 0 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
SCREAMING_SNAKE_CASE = [
"good first issue",
"feature request",
"wip",
]
def lowercase_ ( ) -> int:
"""simple docstring"""
lowercase : Union[str, Any] ... | 717 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 0 |
'''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early o... | 718 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 0 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transfor... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 0 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 720 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor... | 721 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 0 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
SCREAMING_SNAKE_CASE = Mapping[str, np.ndarray]
SCREAMING_SNAKE_CASE = Mapping[str, Any] # Is a n... | 700 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 0 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
SCREAMING_SNAKE_CASE = 3
def lowercase_ ( __A : int ) -> int:
"""simple docstring"""
print('''Generating primitive root of p''' ... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'huggingface/informer-tourism-monthly': (
'https://huggingface... | 702 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : list , __A : list ) -> list:
"""simple docstring"""
if len(__A ) != 2 or len(a[0] ) != 2 or len(__A ) != 2 or len(b[0] ) != 2:
raise Exception('''Matri... | 703 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 704 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
from functools import lru_cache
from math import ceil
SCREAMING_SNAKE_CASE = 100
SCREAMING_SNAKE_CASE = set(range(3, NUM_PRIMES, 2))
primes.add(2)
SCREAMING_SNAKE_CASE = 42
for prime in range(3, ceil(NUM_PRIMES*... | 705 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 0 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import... | 706 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 0 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 707 |
'''simple docstring'''
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 UpperCAmelCase_ ( ... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
SCREAMING_SNAKE_CASE = (3, 9, -11, 0, 7, 5, 1, -1)
SCREAMING_SNAKE_CASE = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class UpperCAmelCase_ :
"""simple... | 708 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 0 |
'''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 = models.Seq... | 709 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, Stab... | 710 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 0 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..tabl... | 711 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-windo... | 712 |
'''simple docstring'''
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 Padd... | 8 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_... | 713 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 0 |
'''simple docstring'''
import requests
SCREAMING_SNAKE_CASE = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='
def lowercase_ ( __A : str ) -> None:
"""simple docstring"""
lowercase : Tuple =requests.get(_NEWS_API + bbc_news_api_k... | 714 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 0 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOC... | 715 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_ernie': ['ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieConfig', 'ErnieOnnxConfig'],
}
t... | 716 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDif... | 717 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 0 |
'''simple docstring'''
import math
import sys
def lowercase_ ( __A : int ) -> int:
"""simple docstring"""
if number != int(__A ):
raise ValueError('''the value of input must be a natural number''' )
if number < 0:
raise ValueError(... | 718 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 0 |
'''simple docstring'''
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : Dict , UpperCAmelCase : Any ) -> Dict:
'''simple docstring'''
lowercase : str =val
lowercase : Tuple =None
lowercase : L... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 0 |
'''simple docstring'''
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 720 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : int = 5_0 ) -> int:
"""simple docstring"""
lowercase : str =[1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile... | 721 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : int = 2_0_0 ) -> int:
"""simple docstring"""
lowercase : Dict =[1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
lowercase : Any =[0] * (pence + 1)
lowercase : Optional[int] =1 # base case: 1 way to... | 700 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def lowercase_ ( __A : Union[str, Any] ) -> Union[str, Any]:
"""simple docstring"""
lowercas... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 0 |
'''simple docstring'''
import random
def lowercase_ ( __A : int ) -> bool:
"""simple docstring"""
lowercase : Dict =num - 1
lowercase : Union[str, Any] =0
while s % 2 == 0:
lowercase : Any =s // 2
t += 1
for _ in range(5 ... | 702 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 0 |
'''simple docstring'''
import argparse
import os
import subprocess
from packaging.version import Version, parse
from accelerate.commands.config.config_args import default_config_file, load_config_from_file
SCREAMING_SNAKE_CASE = 'Run commands across TPU VMs for initial setup before running `accelerate l... | 703 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 0 |
'''simple docstring'''
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_ble... | 704 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 0 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = tuple[float, float, float]
SCREAMING_SNAKE_CASE = tuple[float, float, float]
def lowercase_ ( __A : Pointad , __A : Pointad ) -> Vectorad:
"""simple docstring"""
lowercase ... | 705 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 0 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def lowercase_ ( __A : str = "AAPL" ) -> str:
"""simple docstring"""
lowercase : int =F'https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'
lowercase : List[Any] =Beautifu... | 706 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE = TypeVar('T')
class UpperCAmelCase_ ( Generic[T] ):
"""simple docstring"""
def __init__( self : Union[str, Any] , ... | 707 |
'''simple docstring'''
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 UpperCAmelCase_ ( ... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
SCREAMING_SNAKE_CASE = '2020.9.26'
SCREAMING_SNAKE_CASE = 'xcodz-dot, cclaus, dhruvmanila'
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ... | 708 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 709 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 0 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class UpperCAmelCase_ ( unittest.TestCase ):
"""simple docstring"""
def A__ ( self : Dict ) -> int:
'''simple docstr... | 710 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 8 | 0 |
'''simple docstring'''
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_forward... | 711 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : str , __A : str ) -> int:
"""simple docstring"""
if len(__A ) != len(__A ):
raise ValueError('''String lengths must match!''' )
lowercase : List[Any] =0
for chara, chara in zip(__A ... | 712 |
'''simple docstring'''
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 Padd... | 8 | 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, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import D... | 713 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 0 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'google/umt5-small': 'https://huggingf... | 714 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=__A ):
"""simple docstring"""
UpperCamelCase_ = ['''torch''']
def __init__( self : int , *UpperCAmelCase : Union[str, Any] , **... | 715 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 0 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...te... | 716 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class UpperCAmelCase_ :
"""simple docstring"""
UpperCamelCase_ = field(
default='''codeparrot/codeparrot''' , metadata={'''help''': '''Model name or path o... | 717 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 0 |
'''simple docstring'''
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : list ) -> None:
'''simple docstring'''
lowercase : Union[str, Any] =set_counts
lowerca... | 718 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 0 |
'''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():
fro... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve... | 720 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 0 |
'''simple docstring'''
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
Up... | 721 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
UpperCamelCase_ = ['''image_processor''', '''tokenizer''']
UpperCamelCase_ = ''... | 700 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 0 |
'''simple docstring'''
import argparse
import os
import re
SCREAMING_SNAKE_CASE = 'src/diffusers'
# Pattern that looks at the indentation in a line.
SCREAMING_SNAKE_CASE = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
SCREAMING_SNAKE_CASE = re.compile(r'^... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 0 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import cl... | 702 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE = logging.get_logger(... | 703 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 0 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 704 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 0 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> int:
"""simple docstring"""
while b:
lowercase : Union[str, Any] =b, a % b
return a
def lowercase_ ( __A : int , __A :... | 705 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 0 |
'''simple docstring'''
import heapq
def lowercase_ ( __A : dict ) -> set[int]:
"""simple docstring"""
lowercase : list[list] =[]
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be fil... | 706 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_ten... | 8 | 0 |
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