code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( lowercase_ : list[int | str] ) -> None:
create_state_space_tree(lowercase_ , [] , 0 , [0 for i in range(len(lowercase_ ) )] )
def lowerCAmelCase_( lowercase_ ... | 73 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_f... | 73 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from t... | 73 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : bool = False ) -> list[fl... | 73 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCamelCase_:
'''simple docstring'''
lowercase__ : torch.Tensor # [batch_size x 3]
lowercase__ : torch.Tensor # [batch_size x 3]
l... | 73 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCamelCase_:
'''simple docstring'''
def __init__( self ):
_lowerCamelCase = ''''''
_lowerCamelCase = ''''''
_lowerCam... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : str ) -> str:
return "".join(chr(ord(lowercase_ ) - 32 ) if '''a''' <= char <= '''z''' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 73 |
"""simple docstring"""
import os
from collections.abc import Iterator
def lowerCAmelCase_( lowercase_ : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(lowercase_ ):
_lowerCamelCase = [d for d in dir_names if d != '''scripts''' and... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : float , lowercase_ : float , lowercase_ : float , ) -> float:
_lowerCamelCase = [redshift, radiation_density, matte... | 73 |
"""simple docstring"""
import os
import sys
__SCREAMING_SNAKE_CASE : Dict = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,... | 73 | 1 |
"""simple docstring"""
from manim import *
class lowerCamelCase_( A__ ):
'''simple docstring'''
def snake_case__ ( self ):
_lowerCamelCase = Rectangle(height=0.5 , width=0.5 )
_lowerCamelCase = Rectangle(height=0.2_5 , widt... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : List[str] = {
'''configuration_vision_encoder_decoder''': ['''Vis... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int ) -> int:
while b:
_lowerCamelCase , _lowerCamelCase = b, a % b
return a
def lowerCAmelCase_( lowercase_ : int , lowercase_ : ... | 73 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import random
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ = None ):
_lowerCamelCase = value
_lowerCamelCase = random()
_lowe... | 73 |
"""simple docstring"""
import qiskit
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int ) -> qiskit.result.counts.Counts:
_lowerCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
... | 73 | 1 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCAmelCase_( lowercase_ : Union[str, Any] ) -> int:
# This defines a "chinese character" as anything in the CJK Unicode block:
# h... | 73 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : List[str] ) -> Optional[Any]:
_lowerCamelCase = len(lowercase_ )
while cur > 1:
# Find the maximum number in arr
_lowerCamelCase = arr.index(max(arr[0:cur] ) )
# Reve... | 73 | 1 |
"""simple docstring"""
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_availabl... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Any = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abej... | 73 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def lowerCAmelCase_( lowercase_ : An... | 73 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__SCREAMING... | 73 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Optional[Any] = {
'''caidas/swin2sr-classicalsr-x2-64''': (
'''https://hugging... | 73 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def lowerCAmelCase_( lowercase_ : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowercase_ , 0 , lowercase_ , args=(lo... | 73 | 1 |
"""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():
import jax... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_blenderbot... | 73 | 1 |
"""simple docstring"""
import socket
def lowerCAmelCase_( ) -> Optional[Any]:
_lowerCamelCase = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCamelCase = socket.gethostname()
_lowerCamelCase = 1_23_12
sock.connect((host, port) )
soc... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Dict = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-s... | 73 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_i... | 73 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from t... | 73 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxCo... | 73 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
__SC... | 73 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( lowercase_ : list , lowercase_ : int ) -> Tuple:
# Checks if the entire collection has been sorted
if len(lowercase_ ) <= 1 or n <= 1:
return
insert_next(lowercas... | 73 | 1 |
"""simple docstring"""
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''microsoft/trocr-base-handwritten''': (
'''https... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : list ) -> list:
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_lowerCamelCase = []
def generate(lowercase_ : int , lowercase_ : list ):
_l... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : str = {}
try:
if not is_sentencepiece_available(... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( lowercase_ : Dict , lowercase_ : Tuple , lowercase_ : Tuple , lowercase_ : Union[str, Any] ) -> Any: # noqa: E741
while r - l > 1:
_lowerCamelCa... | 73 |
"""simple docstring"""
import argparse
from collections import defaultdict
def lowerCAmelCase_( lowercase_ : str , lowercase_ : Dict , lowercase_ : Tuple , lowercase_ : str , lowercase_ : str ) -> Optional[int]:
_low... | 73 | 1 |
"""simple docstring"""
from math import isclose, sqrt
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : float ) -> tuple[float, float, float]:
_lowerCamelCase = point_y / 4 / point_x
_lowerCamelCase = 2 *... | 73 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def lowerCAmelCase_( lowercase_ : Optional[int] ) -> int:
return choice(lowercase_ )
def lowerCAmelCase_( lowercase_ : list[int] , lowercase_ : int ... | 73 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
__SC... | 73 | 1 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING... | 73 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_f... | 73 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__SCREAMING_SNAKE_CASE : List[str] = {
'''configuration_audio_spectrogram_transformer''': [
'''AUDIO_SPECTROGRAM_TRANSFORM... | 73 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : bool = False ) -> list[fl... | 73 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowerCamelCase_:
'''simple docstring'''
lowercase__ : Optional[str] = field(
default='codeparrot/codeparrot', metadata={'help': 'Model name or path of model t... | 73 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCamelCase_:
'''simple docstring'''
def __init__( self ):
_lowerCamelCase = ''''''
_lowerCamelCase = ''''''
_lowerCam... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int = 10**9 ) -> int:
_lowerCamelCase = 1
_lowerCamelCase = 2
_lowerCamelCase = 0
_lowerCamelCase = 0
_lowerCamelCase = 0
while perimeter <= max_perimeter:
perime... | 73 |
"""simple docstring"""
import os
from collections.abc import Iterator
def lowerCAmelCase_( lowercase_ : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(lowercase_ ):
_lowerCamelCase = [d for d in dir_names if d != '''scripts''' and... | 73 | 1 |
"""simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.... | 73 |
"""simple docstring"""
import os
import sys
__SCREAMING_SNAKE_CASE : Dict = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,... | 73 | 1 |
"""simple docstring"""
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
__SCREAMING_SNAKE_CASE : Union[str, Any] = {
'''E''': 12.70,
'''T''': 9.06,
'''A''': 8.17,
'''O''': 7.51,
'''I''': 6.97,
'''N''': 6.75,
'''S''': 6.33,
'''H''':... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : List[str] = {
'''configuration_vision_encoder_decoder''': ['''Vis... | 73 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
__SCREAMING_SNAKE_CASE : Any = logging.... | 73 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 73 | 1 |
"""simple docstring"""
from math import factorial, radians
def lowerCAmelCase_( lowercase_ : float , lowercase_ : int = 18 , lowercase_ : int = 10 ) -> float:
_lowerCamelCase = angle_in_degrees - ((angle_in_degrees // 3_6_0.0) * 3_6_0.0)
... | 73 |
"""simple docstring"""
import qiskit
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int ) -> qiskit.result.counts.Counts:
_lowerCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int ) -> float:
return base * power(lowercase_ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('''Raise base to the power of exponent using recursion...'... | 73 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : List[str] ) -> Optional[Any]:
_lowerCamelCase = len(lowercase_ )
while cur > 1:
# Find the maximum number in arr
_lowerCamelCase = arr.index(max(arr[0:cur] ) )
# Reve... | 73 | 1 |
"""simple docstring"""
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Any = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abej... | 73 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFe... | 73 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__SCREAMING... | 73 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
c... | 73 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def lowerCAmelCase_( lowercase_ : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowercase_ , 0 , lowercase_ , args=(lo... | 73 | 1 |
"""simple docstring"""
from functools import lru_cache
def lowerCAmelCase_( lowercase_ : int ) -> set:
_lowerCamelCase = 2
_lowerCamelCase = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.ad... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_blenderbot... | 73 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Dict = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-s... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Dict = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-s... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : float , lowercase_ : list[float] ) -> float:
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows list cann... | 73 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from t... | 73 | 1 |
"""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 numpy as np
import tensorflow as tf
from transformers impor... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxCo... | 73 | 1 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int , lowercase_ : List[str] ) -> Dict:
_lowerCamelCase = {
'''en''': '''Machine ... | 73 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( lowercase_ : list , lowercase_ : int ) -> Tuple:
# Checks if the entire collection has been sorted
if len(lowercase_ ) <= 1 or n <= 1:
return
insert_next(lowercas... | 73 | 1 |
"""simple docstring"""
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
_lowerCamelCase = len(lowerCamelCase__ )
_lowerCamelCase = [0] * len_array
if len_array > 0:
_lowerCamelCase ... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''microsoft/trocr-base-handwritten''': (
'''https... | 73 | 1 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowerCAmelCase_( )... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : str = {}
try:
if not is_sentencepiece_available(... | 73 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
__SCREAMING_SNAKE_CASE : Optional[Any] = datasets.utils.logging.get_logger(__name__... | 73 |
"""simple docstring"""
import argparse
from collections import defaultdict
def lowerCAmelCase_( lowercase_ : str , lowercase_ : Dict , lowercase_ : Tuple , lowercase_ : str , lowercase_ : str ) -> Optional[int]:
_low... | 73 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__SCREAMING_SNAKE_CASE : Optional[Any] = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMO... | 73 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is... | 73 | 1 |
"""simple docstring"""
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
__SCREAMING_SNAKE_CASE : Any = yaml.safe_load(
'''\
name: ""
allow_empty: false
allow_empty_text: t... | 73 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
__SC... | 73 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def lowerCAmelCase_( lowercase_ : List[Any] ) -> Tuple:
if "cls_token" in name:
_lowerCamelCase ... | 73 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_f... | 73 | 1 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__SCREAMING... | 73 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : bool = False ) -> list[fl... | 73 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : Any = {
'''configuration_blip_2''': [
'''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Blip2Config''',
'... | 73 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCamelCase_:
'''simple docstring'''
def __init__( self ):
_lowerCamelCase = ''''''
_lowerCamelCase = ''''''
_lowerCam... | 73 | 1 |
"""simple docstring"""
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 lowerCamelCase_( A__ ):
... | 73 |
"""simple docstring"""
import os
from collections.abc import Iterator
def lowerCAmelCase_( lowercase_ : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(lowercase_ ):
_lowerCamelCase = [d for d in dir_names if d != '''scripts''' and... | 73 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE : List[str] = logging... | 73 |
"""simple docstring"""
import os
import sys
__SCREAMING_SNAKE_CASE : Dict = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,... | 73 | 1 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def lowerCAmelCase_( ) -> Optional[int]:
_lowerCamelCase = HfArgumentParser(lowercase_ )
_lowerCamelCase = parser.parse_args_into_dataclasses()[0]
_lowerC... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : List[str] = {
'''configuration_vision_encoder_decoder''': ['''Vis... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int ) -> int:
_lowerCamelCase = [1]
_lowerCamelCase , _lowerCamelCase , _lowerCamelCase = 0, 0, 0
_lowerCamelCase = ugly_nums[ia] * 2
_lowerCamelCase = ugly_nums[ia]... | 73 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 73 | 1 |
"""simple docstring"""
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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... | 73 |
"""simple docstring"""
import qiskit
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int ) -> qiskit.result.counts.Counts:
_lowerCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
... | 73 | 1 |
"""simple docstring"""
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,
)
__SCREAMING_SNAKE_CASE : List[Any] = pytest.mark.integration
@pytest... | 73 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : List[str] ) -> Optional[Any]:
_lowerCamelCase = len(lowercase_ )
while cur > 1:
# Find the maximum number in arr
_lowerCamelCase = arr.index(max(arr[0:cur] ) )
# Reve... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int = 50 ) -> int:
_lowerCamelCase = [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_length +... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Any = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abej... | 73 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowerCamelCase_( metaclass=A__ ):
'''simple docstring'''
lowercase__ : int = ['torch', 'torchsde']
def __init__( self , *lowerCamelCase__ , **lowerCamelCase__ ):
... | 73 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__SCREAMING... | 73 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 73 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def lowerCAmelCase_( lowercase_ : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowercase_ , 0 , lowercase_ , args=(lo... | 73 | 1 |
"""simple docstring"""
from math import ceil
def lowerCAmelCase_( lowercase_ : List[str] , lowercase_ : str ) -> List[Any]:
_lowerCamelCase = list(range(0 , lowercase_ ) )
_lowerCamelCase = [item for sublist in list(device_map.va... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_blenderbot... | 73 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Dict = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-s... | 73 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
__SCREAMING_SNAKE_CASE : int ... | 73 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from t... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__SCREAMING_SNAKE_CASE : List[str] = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxCo... | 73 | 1 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_atten... | 73 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( lowercase_ : list , lowercase_ : int ) -> Tuple:
# Checks if the entire collection has been sorted
if len(lowercase_ ) <= 1 or n <= 1:
return
insert_next(lowercas... | 73 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Tuple = {
'''google/pix2struct-textcap... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''microsoft/trocr-base-handwritten''': (
'''https... | 73 | 1 |
"""simple docstring"""
import os
from collections.abc import Iterator
def lowerCAmelCase_( lowercase_ : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(lowercase_ ):
_lowerCamelCase = [d for d in dir_names if d != '''scripts''' and... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : str = {}
try:
if not is_sentencepiece_available(... | 73 | 1 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def lowerCAmelCase_( lowercase_ : Tuple , lowercase_ : Any , lowercase_ : List[str] , lowercase_ : str ) -> Any:
_lowerCamelCase = sorted(zip(l... | 73 |
"""simple docstring"""
import argparse
from collections import defaultdict
def lowerCAmelCase_( lowercase_ : str , lowercase_ : Dict , lowercase_ : Tuple , lowercase_ : str , lowercase_ : str ) -> Optional[int]:
_low... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCAmelCase_( lowercase_ : str ) -> None:
_lowerCamelCase , _lowerCamelCase = analyze_text(lowercase_ )
_low... | 73 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is... | 73 | 1 |
"""simple docstring"""
import argparse
import os
import re
__SCREAMING_SNAKE_CASE : Union[str, Any] = '''src/transformers'''
# Pattern that looks at the indentation in a line.
__SCREAMING_SNAKE_CASE : List[Any] = re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 73 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
__SC... | 73 | 1 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : List[str] = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def lowerCAmelCase_( lowercase_ : int ) -> int:
_lowerCamelCase = 0
while number:
# Increased Speed Slightly by... | 73 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_f... | 73 | 1 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
__SCREAMING_SNAKE_CAS... | 73 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : bool = False ) -> list[fl... | 73 | 1 |
"""simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
__SCREAMING_SNAKE_CASE : Dict = argparse.ArgumentParser()
parser.add_argument(
'''--checkpoint_path''', defaul... | 73 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCamelCase_:
'''simple docstring'''
def __init__( self ):
_lowerCamelCase = ''''''
_lowerCamelCase = ''''''
_lowerCam... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : bool = False ) -> list[fl... | 73 |
"""simple docstring"""
import os
from collections.abc import Iterator
def lowerCAmelCase_( lowercase_ : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(lowercase_ ):
_lowerCamelCase = [d for d in dir_names if d != '''scripts''' and... | 73 | 1 |
"""simple docstring"""
import copy
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 : Optional... | 73 |
"""simple docstring"""
import os
import sys
__SCREAMING_SNAKE_CASE : Dict = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,... | 73 | 1 |
"""simple docstring"""
from math import ceil
def lowerCAmelCase_( lowercase_ : int = 10_01 ) -> int:
_lowerCamelCase = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
_lowerCamelCase = 2 * i + 1
_lowerCamelCase = 2 * i
... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : List[str] = {
'''configuration_vision_encoder_decoder''': ['''Vis... | 73 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : int = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-... | 73 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 73 | 1 |
"""simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__SCREAMING_SNAKE_CASE : List[Any] ... | 73 |
"""simple docstring"""
import qiskit
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int ) -> qiskit.result.counts.Counts:
_lowerCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : str ) -> str:
if not all(char in '''01''' for char in bin_string ):
raise ValueError('''Non-binary value was passed to the function''' )
if not bin_string:
raise ValueError('''Empty string was p... | 73 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : List[str] ) -> Optional[Any]:
_lowerCamelCase = len(lowercase_ )
while cur > 1:
# Find the maximum number in arr
_lowerCamelCase = arr.index(max(arr[0:cur] ) )
# Reve... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
_lowerCamelCase = list_of_points
# Degree determines the f... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Any = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abej... | 73 | 1 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
f... | 73 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__SCREAMING... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int ) -> int:
if not isinstance(lowercase_ , lowercase_ ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
retu... | 73 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def lowerCAmelCase_( lowercase_ : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowercase_ , 0 , lowercase_ , args=(lo... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or not...''')
__... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_blenderbot... | 73 | 1 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__SCREAMING_SNAKE_CASE : Optional[... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Dict = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-s... | 73 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGE... | 73 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from t... | 73 | 1 |
"""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_avai... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Dict = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxCo... | 73 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__SCREAMING_SNAKE_CASE : int = {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}
try:
if not... | 73 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( lowercase_ : list , lowercase_ : int ) -> Tuple:
# Checks if the entire collection has been sorted
if len(lowercase_ ) <= 1 or n <= 1:
return
insert_next(lowercas... | 73 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
__SCREAMING_SNAKE_CASE : List[Any] = logging.ge... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''microsoft/trocr-base-handwritten''': (
'''https... | 73 | 1 |
"""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,
Au... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : str = {}
try:
if not is_sentencepiece_available(... | 73 | 1 |
"""simple docstring"""
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase_( *lowercase_ : List[Any] , lowercase_ : Optional[Union[Dict, Any]] = None , lowercase_ : Tuple=True , lower... | 73 |
"""simple docstring"""
import argparse
from collections import defaultdict
def lowerCAmelCase_( lowercase_ : str , lowercase_ : Dict , lowercase_ : Tuple , lowercase_ : str , lowercase_ : str ) -> Optional[int]:
_low... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int ) -> list[int]:
if length <= 0 or not isinstance(lowercase_ , lowercase_ ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in range(lowercase_ )... | 73 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is... | 73 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''microsoft/trocr-base-handwritten''': (
'''https... | 73 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
__SC... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int ) -> "list[int]":
if upper_limit < 0:
raise ValueError('''Limit for the Catalan sequence must be ≥ 0''' )
_lowerCamelCase = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
_lowerCame... | 73 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_f... | 73 | 1 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'''The `image_to_image.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionImg2ImgPipeline` instead.'''
)
| 73 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : bool = False ) -> list[fl... | 73 | 1 |
"""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 Decoder... | 73 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCamelCase_:
'''simple docstring'''
def __init__( self ):
_lowerCamelCase = ''''''
_lowerCamelCase = ''''''
_lowerCam... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__SCREAMING_SNAKE_CASE : Any = TypeVar('''T''')
class lowerCamelCase_( Generic[T] ):
'''simple docstring'''
def __init__( self... | 73 |
"""simple docstring"""
import os
from collections.abc import Iterator
def lowerCAmelCase_( lowercase_ : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(lowercase_ ):
_lowerCamelCase = [d for d in dir_names if d != '''scripts''' and... | 73 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_f... | 73 |
"""simple docstring"""
import os
import sys
__SCREAMING_SNAKE_CASE : Dict = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,... | 73 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : str = {
'''configuration_lxmert''': ['''LXMERT_PRETRAINED_C... | 73 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : List[str] = {
'''configuration_vision_encoder_decoder''': ['''Vis... | 73 | 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 .toke... | 73 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 73 | 1 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__SCREAMING_SNAKE_CASE : Any = ... | 73 |
"""simple docstring"""
import qiskit
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int ) -> qiskit.result.counts.Counts:
_lowerCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
... | 73 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__SCREAMING_SNAKE_CASE : Union... | 73 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : List[str] ) -> Optional[Any]:
_lowerCamelCase = len(lowercase_ )
while cur > 1:
# Find the maximum number in arr
_lowerCamelCase = arr.index(max(arr[0:cur] ) )
# Reve... | 73 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def lowerCAmelCase_( lowercase_ : list , lowercase_ : list ) -> list:
if len(lowercase_ ) != 2 or len(a[0] ) != 2 or len(lowercase_ ) != 2 or len(b[0] ) != 2:
ra... | 73 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Any = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abej... | 73 | 1 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : float , lowercase_ : int ) -> float:
if digit_amount > 0:
return round(number - int(lowercase_ ) , lowercase_ )
return number - int(lowercase_ )
if __name__ == "__main__":
... | 73 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__SCREAMING... | 73 | 1 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE : str = logging.g... | 73 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def lowerCAmelCase_( lowercase_ : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowercase_ , 0 , lowercase_ , args=(lo... | 73 | 1 |
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