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"""
def _a ( UpperCAmelCase__ ) -> bool:
__SCREAMING_SNAKE_CASE = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def _a ( UpperCAmelCase__ = 50_00 ) -> int:
__SCREAMING_SNAKE_CASE = [(i * (3 * i - 1)) // ... | 717 |
"""simple docstring"""
import math
lowerCAmelCase__ =10
lowerCAmelCase__ =7
lowerCAmelCase__ =BALLS_PER_COLOUR * NUM_COLOURS
def _a ( UpperCAmelCase__ = 20 ) -> str:
__SCREAMING_SNAKE_CASE = math.comb(UpperCAmelCase__ , UpperCAmelCase__ ... | 690 | 0 |
import string
def _a ( UpperCAmelCase__ ) -> None:
for key in range(len(string.ascii_uppercase ) ):
__SCREAMING_SNAKE_CASE = ''''''
for symbol in message:
if symbol in string.ascii_uppercase:
__SCREAMING_... | 718 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_avail... | 690 | 0 |
"""simple docstring"""
def _a ( UpperCAmelCase__ ) -> int:
assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), f"""The input value of [n={number}] is not an integer"""
if number == 1:
return 2
elif number < 1:
__SCREAMING_SNAKE_CASE ... | 719 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
lowerCAmelCase__ =list[list[float | int]]
def _a ( UpperCAmelCase__ , UpperCAmelCase__ ) -> Matrix:
__SCREAMING_SNAKE_CASE = len(UpperCAmelCase__ )
__S... | 690 | 0 |
"""simple docstring"""
from __future__ import annotations
lowerCAmelCase__ =10
def _a ( UpperCAmelCase__ ) -> list[int]:
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = max(UpperCAmelCase__ )
while placement <= max_digit:
... | 720 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _a ( UpperCAmelCase__ = "isbn/0140328726" ) -> dict:
__SCREAMING_SNAKE_CASE = olid.strip().strip('''/''' ) # Remove leading/trailing w... | 690 | 0 |
"""simple docstring"""
from __future__ import annotations
def _a ( UpperCAmelCase__ , UpperCAmelCase__ = None , UpperCAmelCase__ = None ) -> None:
if start is None:
__SCREAMING_SNAKE_CASE = 0
if end is None:
__SCREAMING_SNAKE_CASE ... | 721 |
"""simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
... | 690 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, 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,
... | 700 |
"""simple docstring"""
def _a ( UpperCAmelCase__ ) -> str:
__SCREAMING_SNAKE_CASE = ''''''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def _a ( UpperCAmel... | 690 | 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
lowerCAmelCase__ =logging.get_logger(__name__)
lowerCAmelCase__... | 701 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_av... | 690 | 0 |
"""simple docstring"""
from timeit import timeit
lowerCAmelCase__ ={
"MALAYALAM": True,
"String": False,
"rotor": True,
"level": True,
"A": True,
"BB": True,
"ABC": False,
"amanaplanacanalpanama": True, # "a man a plan a canal panama"
}
# Ensure our test data is valid... | 702 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cach... | 690 | 0 |
"""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_... | 703 |
"""simple docstring"""
from __future__ import annotations
lowerCAmelCase__ =8.9_8_8E9 # units = N * m^s * C^-2
def _a ( UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ ) -> dict[str, float]:
__SCREAMING_SNAKE_CASE = abs(c... | 690 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
f... | 704 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
lowerCAmelCase__ =logging.get_logger(__name__)
def _a ( UpperCAmelCase__ ) -> Tuple:... | 690 | 0 |
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing import PolynomialFeat... | 705 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 690 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
lowerCAmelCase__ =logging.get_logger(__name__)
class A__( __magic_name__ ):
def __init__( self : int , *__SCREAMING_... | 706 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A__( unittest.Tes... | 690 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase__ ={
"configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
"tokenization_canine":... | 707 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torc... | 690 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCAmelCase__ ={"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_available():
raise OptionalDepende... | 708 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCAmelCase__ ={"UserAgent": UserAgent().random}
def _a ( UpperCAmelCase__ ) -> dict:
__SCREAMING_SNAKE_CASE ... | 690 | 0 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def _a ( UpperCAmelCase__ ) -> Dict:
__SCREAMING_SNAKE_CASE = test_file... | 709 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
lowerCAmelCase__ ="\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives ... | 690 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import Re... | 710 |
"""simple docstring"""
def _a ( UpperCAmelCase__ = 10**9 ) -> int:
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = 2
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = 0
... | 690 | 0 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.INFO
)
lowerCAmelCase__ =logging.getLogger(__name__)
if __name__ ==... | 711 |
"""simple docstring"""
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.prepr... | 690 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.g... | 712 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_conf... | 690 | 0 |
"""simple docstring"""
import math
def _a ( UpperCAmelCase__ , UpperCAmelCase__ ) -> float:
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensity
if ang... | 713 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase__ =logging.get_logger(__name__)
lowerCAmelCase__ ={
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/mai... | 690 | 0 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _a ( UpperCAmelCase__ = "isbn/0140328726" ) -> dict:
__SCREAMING_SNAKE_CASE = olid.strip().strip('''/''' ) # Remove leading/trailing w... | 714 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 690 | 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,
StableDi... | 715 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase__ ={
"configuration_altclip": [
"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AltCLIPConfig",
... | 690 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class A__:
def __init__( self : List[str] , __SCREAMING_SNAKE_CASE : int=2 , __SCREAMING_SNAKE_CASE... | 716 |
"""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_u... | 690 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torc... | 717 |
"""simple docstring"""
import math
lowerCAmelCase__ =10
lowerCAmelCase__ =7
lowerCAmelCase__ =BALLS_PER_COLOUR * NUM_COLOURS
def _a ( UpperCAmelCase__ = 20 ) -> str:
__SCREAMING_SNAKE_CASE = math.comb(UpperCAmelCase__ , UpperCAmelCase__ ... | 690 | 0 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tra... | 718 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_avail... | 690 | 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():
... | 719 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
lowerCAmelCase__ =list[list[float | int]]
def _a ( UpperCAmelCase__ , UpperCAmelCase__ ) -> Matrix:
__SCREAMING_SNAKE_CASE = len(UpperCAmelCase__ )
__S... | 690 | 0 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCAmelCase__ =False
class A__( unitte... | 720 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _a ( UpperCAmelCase__ = "isbn/0140328726" ) -> dict:
__SCREAMING_SNAKE_CASE = olid.strip().strip('''/''' ) # Remove leading/trailing w... | 690 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
Ada... | 721 |
"""simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
... | 690 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class A :
def __init__( self , snake_case_ ) -> None:
_a = value
_a = None
_a = None
class A :
... | 691 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require... | 691 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : Tuple = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 691 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Tuple = logging.get_logger(__name__)
__snake_case : int = {
"facebook/wav2vec2-base-960h": "https://huggingface.c... | 691 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImagePr... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number | (1 << position)
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number & ~(1 << position)
def _lowercase ( lowerCamelCase_... | 691 | 1 |
'''simple docstring'''
import math
import qiskit
def _lowercase ( lowerCamelCase__ : int = 1, lowerCamelCase__ : int = 1, lowerCamelCase__ : int = 1 ):
if (
isinstance(lowerCamelCase__, lowerCamelCase__ )
or isinstance(lowerCamelCase__, lowerCamelCase__ )... | 691 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 691 | 1 |
'''simple docstring'''
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__snake_case : Optional[Any] = logging.get_logger(__name__)
def _lowercase ( lowe... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[list] ):
_a = current_set.copy()
for row_index, row in enumerate(lowerCamelCase__ ):
_a = row[0]
for column_index, column in enumerate(lowerCamelCase__ ):
if mag... | 691 | 1 |
'''simple docstring'''
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
im... | 691 |
'''simple docstring'''
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unorde... | 691 | 1 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require... | 691 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__snake_case : Optional[int] = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n c... | 691 | 1 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
__... | 691 |
'''simple docstring'''
class A :
def __init__( self ) -> List[str]:
_a = 0
_a = 0
_a = {}
def __lowerCAmelCase ( self , snake_case_ ) -> int:
if vertex not in self.adjacency:
... | 691 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A ( unittest.TestCase ):
... | 691 |
'''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,
f... | 691 | 1 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
__snake_case : Union[st... | 691 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
__snake_case : Union[st... | 691 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transforme... | 691 |
'''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 691 | 1 |
'''simple docstring'''
from collections.abc import Generator
from math import sin
def _lowercase ( lowerCamelCase__ : bytes ):
if len(lowerCamelCase__ ) != 32:
raise ValueError("Input must be of length 32" )
_a = b""
for i in [3, 2, 1, 0]:
l... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[int], lowerCamelCase__ : list[int], lowerCamelCase__ : int ):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(lowerCamelCase__ ) )
def _lowercas... | 691 | 1 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def _lowercase ( lowerCamelCase__ : Tuple ):
_a = [
"encoder.version",
"decoder.version",
"model.en... | 691 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class A :
def __init__( self , snake_case_ ) -> Optional[int]:
_a = str(id_ )
_a = None
_a = None
_a = ... | 691 | 1 |
'''simple docstring'''
# limitations under the License.
# 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 .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils... | 691 |
'''simple docstring'''
__snake_case : List[str] = "Tobias Carryer"
from time import time
class A :
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_=int(time() ) ) -> str: # noqa: B008
_a = mul... | 691 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
class A ( a ):
__UpperCAmelCase : List[str] = """bert-generation"""
def __init__( self , snake_case_=5_0_3_5_8 , snake_case_=1_0_2_4 , snake_case_=2_4 , snake_case_=... | 691 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small... | 691 | 1 |
'''simple docstring'''
from math import factorial
def _lowercase ( lowerCamelCase__ : int = 100 ):
return sum(map(lowerCamelCase__, str(factorial(lowerCamelCase__ ) ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the Number: ").strip())))
... | 691 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : int = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],... | 691 | 1 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_a... | 691 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A ( metaclass=a ):
__UpperCAmelCase : int = ["""torch""", """scipy"""]
def __init__( self , *snake_case_ , **snake_case_ ) -> Tuple:
requires_backends(self ... | 691 | 1 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
f... | 691 |
'''simple docstring'''
__snake_case : Dict = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
... | 691 | 1 |
'''simple docstring'''
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class A :
__UpperCAmelCase : float
__UpperCAmelCase : TreeNode | None = None
__UpperCAmelCase : TreeNode | None = None
def _lowerc... | 691 |
'''simple docstring'''
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet imp... | 691 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fr... | 691 |
'''simple docstring'''
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCal... | 691 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
__snake_case : Dict = ["small", "medium", "large"]
__snake_case : Optional[int] = "lm_head.decoder.weight"
__snake_case : Optional[int] = "lm_... | 691 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def _lowercase ( lowerCamelCase__ : Any, lowerCamelCase__ : Optional[int], lowerCamelCase__ : Dict, lowerCamelCase__ : List[str] ):
_a = {
"en": "Machine learning is ... | 691 | 1 |
'''simple docstring'''
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 691 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp impor... | 691 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A ( metaclass=a ):
__UpperCAmelCase : int = ["""torch""", """scipy"""]
def __init__( self , *snake_case_ , **snake_case_ ) -> Tuple:
requires_backends(self ... | 691 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require... | 691 | 1 |
'''simple docstring'''
import enum
import shutil
import sys
__snake_case , __snake_case : List[Any] = shutil.get_terminal_size()
__snake_case : int = {"UP": "A", "DOWN": "B", "RIGHT": "C", "LEFT": "D"}
class A ( enum.Enum ):
__UpperCAmelCase ... | 691 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Tuple = logging.get_logger(__name__)
__snake_case : int = {
"facebook/wav2vec2-base-960h": "https://huggingface.c... | 691 | 1 |
'''simple docstring'''
import collections
import importlib.util
import os
import re
from pathlib import Path
__snake_case : List[str] = "src/transformers"
# Matches is_xxx_available()
__snake_case : Optional[Any] = re.compile(R"is\_([a-z_]*)_available()")
# Catches a o... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number | (1 << position)
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number & ~(1 << position)
def _lowercase ( lowerCamelCase_... | 691 | 1 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[list] ):
_a = current_set.copy()
for row_index, row in enumerate(lowerCamelCase__ ):
_a = row[0]
for column_index, column in enumerate(lowerCamelCase__ ):
if mag... | 691 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 691 | 1 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list ):
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
_a = []
def generate(lowerCamelCase__ : int, lowerCamelCase__ : list ):
if k == 1:
res.a... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[list] ):
_a = current_set.copy()
for row_index, row in enumerate(lowerCamelCase__ ):
_a = row[0]
for column_index, column in enumerate(lowerCamelCase__ ):
if mag... | 691 | 1 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__snake_case : Optional[int] = "\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin... | 691 |
'''simple docstring'''
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unorde... | 691 | 1 |
'''simple docstring'''
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
f... | 691 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__snake_case : Optional[int] = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n c... | 691 | 1 |
'''simple docstring'''
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
__snake_case : List[Any] = logging.get_logger(__name__) # pylint: disable=inv... | 691 |
'''simple docstring'''
class A :
def __init__( self ) -> List[str]:
_a = 0
_a = 0
_a = {}
def __lowerCAmelCase ( self , snake_case_ ) -> int:
if vertex not in self.adjacency:
... | 691 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case : Dict = logging.get_logger(__name__)
__snake_case : Tuple ... | 691 |
'''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,
f... | 691 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.ut... | 691 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
__snake_case : Union[st... | 691 | 1 |
'''simple docstring'''
import argparse
import os
import re
__snake_case : str = "src/diffusers"
# Pattern that looks at the indentation in a line.
__snake_case : Optional[int] = re.compile(R"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
__snake_c... | 691 |
'''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 691 | 1 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number | (1 << position)
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number & ~(1 << position)
def _lowercase ( lowerCamelCase_... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[int], lowerCamelCase__ : list[int], lowerCamelCase__ : int ):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(lowerCamelCase__ ) )
def _lowercas... | 691 | 1 |
'''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 691 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class A :
def __init__( self , snake_case_ ) -> Optional[int]:
_a = str(id_ )
_a = None
_a = None
_a = ... | 691 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A ( a ):
__UpperCAmelCase : ... | 691 |
'''simple docstring'''
__snake_case : List[str] = "Tobias Carryer"
from time import time
class A :
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_=int(time() ) ) -> str: # noqa: B008
_a = mul... | 691 | 1 |
'''simple docstring'''
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__snake_case : Optional[Any] = False
class A ( unittest.TestCase ):
... | 691 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small... | 691 | 1 |
'''simple docstring'''
import string
from math import logaa
def _lowercase ( lowerCamelCase__ : str, lowerCamelCase__ : str ):
_a = document.translate(
str.maketrans("", "", string.punctuation ) ).replace("\n", "" )
_a = document_w... | 691 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : int = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],... | 691 | 1 |
'''simple docstring'''
import math
import unittest
def _lowercase ( lowerCamelCase__ : int ):
assert isinstance(lowerCamelCase__, lowerCamelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
... | 691 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A ( metaclass=a ):
__UpperCAmelCase : int = ["""torch""", """scipy"""]
def __init__( self , *snake_case_ , **snake_case_ ) -> Tuple:
requires_backends(self ... | 691 | 1 |
'''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class A ( enum.Enu... | 691 |
'''simple docstring'''
__snake_case : Dict = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
... | 691 | 1 |
'''simple docstring'''
from __future__ import annotations
class A :
def __init__( self , snake_case_=None ) -> Any:
_a = data
_a = None
def __repr__( self ) -> Optional[int]:
_a = []
_a ... | 691 |
'''simple docstring'''
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet imp... | 691 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import fl... | 691 |
'''simple docstring'''
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCal... | 691 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, Ten... | 691 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def _lowercase ( lowerCamelCase__ : Any, lowerCamelCase__ : Optional[int], lowerCamelCase__ : Dict, lowerCamelCase__ : List[str] ):
_a = {
"en": "Machine learning is ... | 691 | 1 |
'''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 691 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp impor... | 691 | 1 |
'''simple docstring'''
from datetime import datetime
import requests
def _lowercase ( lowerCamelCase__ : str ):
_a = "https://downloadgram.net/wp-json/wppress/video-downloader/video?url="
_a = requests.get(base_url + url ).json()[0]["urls"][0]["src"]
... | 691 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require... | 691 | 1 |
'''simple docstring'''
import socket
def _lowercase ( ):
_a = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
_a = socket.gethostname()
_a = 12_312
sock.connect((host, port) )
sock.send(b"Hello server!" )
with open("R... | 691 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Tuple = logging.get_logger(__name__)
__snake_case : int = {
"facebook/wav2vec2-base-960h": "https://huggingface.c... | 691 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def _lowercase ( lowerCamelCase__ : str = "https://www.worldometers.info/coronavirus" ):
_a = BeautifulSoup(requests.get(lowerCamelCase__ ).text, "html.parser" )
_a = soup.findAll(... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number | (1 << position)
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number & ~(1 << position)
def _lowercase ( lowerCamelCase_... | 691 | 1 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : Any, lowerCamelCase__ : Any ):
_a = [1]
for i in range(2, lowerCamelCase__ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k out of bounds"
_a = ... | 691 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 691 | 1 |
'''simple docstring'''
from manim import *
class A ( a ):
def __lowerCAmelCase ( self ) -> str:
_a = Rectangle(height=0.5 , width=0.5 )
_a = Rectangle(height=0.25 , width=0.25 )
_a = Rectangle(height=... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[list] ):
_a = current_set.copy()
for row_index, row in enumerate(lowerCamelCase__ ):
_a = row[0]
for column_index, column in enumerate(lowerCamelCase__ ):
if mag... | 691 | 1 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
__snake_case : Dict = ... | 691 |
'''simple docstring'''
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unorde... | 691 | 1 |
'''simple docstring'''
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSample... | 691 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__snake_case : Optional[int] = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n c... | 691 | 1 |
'''simple docstring'''
import torch
from torch import nn
class A ( nn.Module ):
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_ , snake_case_=1 , snake_case_=False ) -> List[Any]:
super().__init__()
... | 691 |
'''simple docstring'''
class A :
def __init__( self ) -> List[str]:
_a = 0
_a = 0
_a = {}
def __lowerCAmelCase ( self , snake_case_ ) -> int:
if vertex not in self.adjacency:
... | 691 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A ( a ):
@staticmethod
@abstractmethod
def __lowerCAmelCase ( snake_case_ ) -> str:
raise NotImplementedError()
@abstractmethod
def __lowe... | 691 |
'''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,
f... | 691 | 1 |
'''simple docstring'''
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_D... | 691 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
__snake_case : Union[st... | 691 | 1 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase__, int(b / 2 ) ) * actual_power(lowerCamelCase__, int(b / 2 ) )
else:
r... | 691 |
'''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 691 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
__snake_case : Optional[Any] = logging.get_logger(__name__)
class A ( a ):
def __init__( self , *snake_case_ , **snake_cas... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[int], lowerCamelCase__ : list[int], lowerCamelCase__ : int ):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(lowerCamelCase__ ) )
def _lowercas... | 691 | 1 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list ):
if not isinstance(lowerCamelCase__, lowerCamelCase__ ):
raise ValueError("Input series is not valid, valid series - [2, 4, 6]" )
if len(lowerCamelCase__ ) == 0:
raise ValueError("Input li... | 691 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class A :
def __init__( self , snake_case_ ) -> Optional[int]:
_a = str(id_ )
_a = None
_a = None
_a = ... | 691 | 1 |
'''simple docstring'''
import numpy
# List of input, output pairs
__snake_case : List[str] = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
__snake_case : Tuple = (((515, 22, 13), 555), ((61, 35, 49), 150)... | 691 |
'''simple docstring'''
__snake_case : List[str] = "Tobias Carryer"
from time import time
class A :
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_=int(time() ) ) -> str: # noqa: B008
_a = mul... | 691 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cu... | 691 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small... | 691 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.util... | 691 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : int = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],... | 691 | 1 |
'''simple docstring'''
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : Tuple = ... | 691 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A ( metaclass=a ):
__UpperCAmelCase : int = ["""torch""", """scipy"""]
def __init__( self , *snake_case_ , **snake_case_ ) -> Tuple:
requires_backends(self ... | 691 | 1 |
'''simple docstring'''
import math
def _lowercase ( lowerCamelCase__ : float, lowerCamelCase__ : float ):
if (
not isinstance(lowerCamelCase__, (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError("power_factor must be a v... | 691 |
'''simple docstring'''
__snake_case : Dict = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
... | 691 | 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_chan... | 691 |
'''simple docstring'''
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet imp... | 691 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet imp... | 691 |
'''simple docstring'''
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCal... | 691 | 1 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 691 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def _lowercase ( lowerCamelCase__ : Any, lowerCamelCase__ : Optional[int], lowerCamelCase__ : Dict, lowerCamelCase__ : List[str] ):
_a = {
"en": "Machine learning is ... | 691 | 1 |
'''simple docstring'''
import sys
def _lowercase ( lowerCamelCase__ : Dict ):
_a = len(lowerCamelCase__ )
_a = [[0 for x in range(lowerCamelCase__ )] for x in range(lowerCamelCase__ )]
_a = [[0 for x in range(lowerCamelCase__ ... | 691 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp impor... | 691 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small... | 691 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require... | 691 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowercase ( lowerCamelCase__ : list[int | str] ):
create_state_space_tree(lowerCamelCase__, [], 0, [0 for i in range(len(lowerCamelCase__ ) )] )
def _lowercase ( lowerCamelCase__ : list[int | s... | 691 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Tuple = logging.get_logger(__name__)
__snake_case : int = {
"facebook/wav2vec2-base-960h": "https://huggingface.c... | 691 | 1 |
'''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_utils... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number | (1 << position)
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number & ~(1 << position)
def _lowercase ( lowerCamelCase_... | 691 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class A :
__UpperCAmelCase : torch.Tensor # [batch_size x 3]
__UpperCAmelCase : torch.Tensor # [batch_size x 3]
__UpperCAmelCase : torch.... | 691 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 691 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : Dict = {
"configuration_time_series_transformer": [
"TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Time... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[list] ):
_a = current_set.copy()
for row_index, row in enumerate(lowerCamelCase__ ):
_a = row[0]
for column_index, column in enumerate(lowerCamelCase__ ):
if mag... | 691 | 1 |
'''simple docstring'''
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 691 |
'''simple docstring'''
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unorde... | 691 | 1 |
'''simple docstring'''
__snake_case : Dict = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
... | 691 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__snake_case : Optional[int] = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n c... | 691 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.