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 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}
try:
... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[str] = BeautifulSoup(requests.get(_lowerCamelCase , params=_lowerCamelCase ).content ... | 658 | 1 |
# 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-2.0
#
# Unless required by appli... | 658 |
def A ( _lowerCamelCase = 1_000_000 ):
'''simple docstring'''
_lowerCAmelCase : Any = 1
_lowerCAmelCase : Optional[Any] = 1
_lowerCAmelCase : List[str] = {1: 1}
for inputa in range(2 , ... | 658 | 1 |
from __future__ import annotations
_snake_case = "#"
class UpperCAmelCase_ :
def __init__( self):
'''simple docstring'''
_lowerCAmelCase : dict = {}
def snake_case__ ( self, __a):
'''simp... | 658 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
_snake_case = "https://openaipublic.azureedg... | 658 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSemanticSegmentation,
Seg... | 658 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple... | 658 | 1 |
def A ( _lowerCamelCase ):
'''simple docstring'''
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(_lowerCamelCase ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__("doctest").tes... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len(_lowerCamelCase )
for i in range(1 , _lowerCamelCase ):
_lowerCAmelCase : List[Any] = collection[i]
... | 658 | 1 |
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogram_diffusion import... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake_case = logging.get_logger(__name__)
_snake_case = {
"microsoft/focalnet-tiny": "https://huggingface.co/microsof... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"caidas/swin2sr-classicalsr-x2-64": (
"https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json"
),
}
class UpperC... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
def count_of_possible_combinations(_lowerCamelCase ) -> int:
if target < 0:
return 0
if target == 0:
... | 658 | 1 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_confi... | 658 |
import string
def A ( _lowerCamelCase ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
_lowerCAmelCase : str = ""
for symbol in message:
if symbol in string.asc... | 658 | 1 |
from __future__ import annotations
from collections.abc import Callable
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase = 100 , ):
'''simple docstring'''
_lowerCAmelCase : Tuple = x_s... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
_lowerCAmelCase : str = BeautifulSoup(requests.get(_lowerCamelCase ).text , "html.parser"... | 658 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
def count_of_possible_combinations(_lowerCamelCase ) -> int:
if target < 0:
return 0
if target == 0:
... | 658 |
from __future__ import annotations
from collections.abc import MutableSequence
class UpperCAmelCase_ :
def __init__( self, __a, __a):
'''simple docstring'''
if len(__a) != degree + 1:
raise ValueError(
... | 658 | 1 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTeste... | 658 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
"xlnet-large-cased": "https://huggingface.co/xlnet... | 658 | 1 |
from __future__ import annotations
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = [True] * limit
_lowerCAmelCase : List[Any] = False
_lowerCAmelCase : List[Any] ... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05) = }''')
| 658 | 1 |
from sklearn.metrics import mean_squared_error
import datasets
_snake_case = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P... | 658 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( a):
lowerCamelCase__ = 'upernet'
def __init__( se... | 658 | 1 |
from __future__ import annotations
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : list[list[int]] = []
_lowerCAmelCase : list[int] = []
_lowerCAmelCase : Any... | 658 |
import baseaa
def A ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def A ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecode(_lowerCamelCas... | 658 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Dict = 0
if start < end:
... | 658 |
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
_snake_case = logging.get_logger(__name__)
_snake_case = {
"facebook/data2vec-vision-base-ft... | 658 | 1 |
from __future__ import annotations
def A ( _lowerCamelCase ):
'''simple docstring'''
return [ord(_lowerCamelCase ) - 96 for elem in plain]
def A ( _lowerCamelCase ):
'''simple docstring'''
return "".join(chr... | 658 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
_snake_case = {
"cola": 2,
"m... | 658 | 1 |
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
_snake_case = logging.get_logger(__name__)
_snake_case = {"vocab_fil... | 658 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
_snake_case = "\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Method for Automatic Evalua... | 658 | 1 |
from __future__ import annotations
def A ( _lowerCamelCase ):
'''simple docstring'''
if not nums:
raise ValueError("List is empty" )
return sum(_lowerCamelCase ) / len(_lowerCamelCase )
if __name__ == "__main__":
import ... | 658 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def A ( _lowerCamelCase , _lowerCamelCase=False ):
'''simple docstring'''
_lowerCAmelCase : Dict = OmegaConf.load(_lowerC... | 658 | 1 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCame... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}
class UpperCAmelCase_ ( a):
l... | 658 | 1 |
def A ( ):
'''simple docstring'''
return [list(range(1_000 - i , -1_000 - i , -1 ) ) for i in range(1_000 )]
_snake_case = generate_large_matrix()
_snake_case = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]... | 658 |
from __future__ import annotations
def A ( _lowerCamelCase ):
'''simple docstring'''
if not nums:
raise ValueError("List is empty" )
return sum(_lowerCamelCase ) / len(_lowerCamelCase )
if __name__ == "__main__":
import ... | 658 | 1 |
from __future__ import annotations
def A ( _lowerCamelCase ):
'''simple docstring'''
if len(_lowerCamelCase ) == 0:
return []
_lowerCAmelCase , _lowerCAmelCase : List[Any] = min(_lowerCamelCase ), max(_lowe... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
if length <= 0 or not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(_lowerCamelCase... | 658 | 1 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 658 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def A ( _lowerCamelCase ):
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def ... | 658 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
"configuration_layoutlmv3": [
"LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MA... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[str] = BeautifulSoup(requests.get(_lowerCamelCase , params=_lowerCamelCase ).content ... | 658 | 1 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class U... | 658 |
def A ( _lowerCamelCase = 1_000_000 ):
'''simple docstring'''
_lowerCAmelCase : Any = 1
_lowerCAmelCase : Optional[Any] = 1
_lowerCAmelCase : List[str] = {1: 1}
for inputa in range(2 , ... | 658 | 1 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( a):
def __init__( self, *__a, **__a):
'''simple docstring'''
wa... | 658 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
_snake_case = "https://openaipublic.azureedg... | 658 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_snake_case = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that wi... | 658 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple... | 658 | 1 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Tuple = hex_num.strip()
if not hex_num:
raise ValueError("No value was passed to the function" )
_lowerCAmelCase : Optional[Any] = ... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len(_lowerCamelCase )
for i in range(1 , _lowerCamelCase ):
_lowerCAmelCase : List[Any] = collection[i]
... | 658 | 1 |
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
_snake_case = False
class UpperCAmelCase_ ( unittest.TestCase):
pass
... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake_case = logging.get_logger(__name__)
_snake_case = {
"microsoft/focalnet-tiny": "https://huggingface.co/microsof... | 658 | 1 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCAmelCase_ ( ... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
def count_of_possible_combinations(_lowerCamelCase ) -> int:
if target < 0:
return 0
if target == 0:
... | 658 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
_snake_case = logging.get_logger(__name__)
_snake_case = {"voc... | 658 |
import string
def A ( _lowerCamelCase ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
_lowerCAmelCase : str = ""
for symbol in message:
if symbol in string.asc... | 658 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_enforce_args(_lowerCamelCase , _lowerCamelCase )
if n == 0:
return 0
_lowerCAmelCase : Optional[Any] = float("-inf" )
f... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
_lowerCAmelCase : str = BeautifulSoup(requests.get(_lowerCamelCase ).text , "html.parser"... | 658 | 1 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.p... | 658 |
from __future__ import annotations
from collections.abc import MutableSequence
class UpperCAmelCase_ :
def __init__( self, __a, __a):
'''simple docstring'''
if len(__a) != degree + 1:
raise ValueError(
... | 658 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
_lowerCAmelCase : List[str] = _modexpt(_lowerCamelCase ... | 658 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
"xlnet-large-cased": "https://huggingface.co/xlnet... | 658 | 1 |
from math import ceil
def A ( _lowerCamelCase = 1_001 ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
_lowerCAmelCase : Dict = ... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05) = }''')
| 658 | 1 |
import argparse
from collections import defaultdict
import yaml
_snake_case = "docs/source/en/_toctree.yml"
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = defaultdict(_lowerCamelCase )
for... | 658 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( a):
lowerCamelCase__ = 'upernet'
def __init__( se... | 658 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from .... | 658 |
import baseaa
def A ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def A ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecode(_lowerCamelCas... | 658 | 1 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def A ( _lo... | 658 |
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
_snake_case = logging.get_logger(__name__)
_snake_case = {
"facebook/data2vec-vision-base-ft... | 658 | 1 |
from random import shuffle
import tensorflow as tf
from numpy import array
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[str] = int(_lowerCamelCase )
assert noofclusters < len(_l... | 658 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
_snake_case = {
"cola": 2,
"m... | 658 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionPipeline,
UnCLIPIma... | 658 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
_snake_case = "\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Method for Automatic Evalua... | 658 | 1 |
def A ( _lowerCamelCase ):
'''simple docstring'''
if len(_lowerCamelCase ) <= 1:
return [tuple(_lowerCamelCase )]
_lowerCAmelCase : Optional[Any] = []
def generate(_lowerCamelCase , _lowerCamelCase ... | 658 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def A ( _lowerCamelCase , _lowerCamelCase=False ):
'''simple docstring'''
_lowerCAmelCase : Dict = OmegaConf.load(_lowerC... | 658 | 1 |
import unittest
from transformers import DonutProcessor
_snake_case = "naver-clova-ix/donut-base"
class UpperCAmelCase_ ( unittest.TestCase):
def snake_case__ ( self):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = ... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}
class UpperCAmelCase_ ( a):
l... | 658 | 1 |
from __future__ import annotations
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
if b == 0:
return (1, 0)
((_lowerCAmelCase) , (_lowerCAmelCase)) : Any = extended_euclid(_lowerCamelCase... | 658 |
from __future__ import annotations
def A ( _lowerCamelCase ):
'''simple docstring'''
if not nums:
raise ValueError("List is empty" )
return sum(_lowerCamelCase ) / len(_lowerCamelCase )
if __name__ == "__main__":
import ... | 658 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : str = 0
_lowerCAmelCase : Optional[int] = len(_lowerCamelCase ) - 1
while left <= right:
# avoid divide... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
if length <= 0 or not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(_lowerCamelCase... | 658 | 1 |
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 658 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def A ( _lowerCamelCase ):
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def ... | 658 | 1 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( a):
lowerCamelCase__ = 'ClapFeatureExtractor'
lowerCamelCase__ = ('RobertaTokenizer', 'RobertaTokenizerFast')
def __init__( self, ... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[str] = BeautifulSoup(requests.get(_lowerCamelCase , params=_lowerCamelCase ).content ... | 658 | 1 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase = 10**-10 ):
'''simple docstring'''
_lowerCAmelCase : Any ... | 658 |
def A ( _lowerCamelCase = 1_000_000 ):
'''simple docstring'''
_lowerCAmelCase : Any = 1
_lowerCAmelCase : Optional[Any] = 1
_lowerCAmelCase : List[str] = {1: 1}
for inputa in range(2 , ... | 658 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple... | 658 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
_snake_case = "https://openaipublic.azureedg... | 658 | 1 |
import heapq
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like ... | 658 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple... | 658 | 1 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
_lowerCAmelCase : str = BeautifulSoup(requests.get(_lowerCamelCase ).text , "html.parser"... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len(_lowerCamelCase )
for i in range(1 , _lowerCamelCase ):
_lowerCAmelCase : List[Any] = collection[i]
... | 658 | 1 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
fr... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake_case = logging.get_logger(__name__)
_snake_case = {
"microsoft/focalnet-tiny": "https://huggingface.co/microsof... | 658 | 1 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class UpperCAmelCase_ ( a , a):
@register_to_config
def __init__( self, *,
__a = 4, __a = 768, __a, __a, ):
... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
def count_of_possible_combinations(_lowerCamelCase ) -> int:
if target < 0:
return 0
if target == 0:
... | 658 | 1 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Dict = args.pruning_method
_lower... | 658 |
import string
def A ( _lowerCamelCase ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
_lowerCAmelCase : str = ""
for symbol in message:
if symbol in string.asc... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
"uclanlp/visualbert-vqa-pre": "https://huggingface.co/u... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
_lowerCAmelCase : str = BeautifulSoup(requests.get(_lowerCamelCase ).text , "html.parser"... | 658 | 1 |
from typing import List
import numpy as np
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[Any] = {key: len(_lowerCamelCase ) for key, value in gen_kwargs.items() if isinstance(_lowerCamelCase , _lowerCame... | 658 |
from __future__ import annotations
from collections.abc import MutableSequence
class UpperCAmelCase_ :
def __init__( self, __a, __a):
'''simple docstring'''
if len(__a) != degree + 1:
raise ValueError(
... | 658 | 1 |
from __future__ import annotations
from math import pi
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError("One and only ... | 658 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
"xlnet-large-cased": "https://huggingface.co/xlnet... | 658 | 1 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( a):
lowerCamelCase__ = (IPNDMScheduler,)
lowerCamelCase__ = (('num_inference_steps', 50),)
def snake_case__ ( ... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05) = }''')
| 658 | 1 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
_snake_case = 5_0000
_snake_case = 5000
_snake_case, _snake_case = os.path.split(__file__)
_snake_case = os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", "... | 658 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( a):
lowerCamelCase__ = 'upernet'
def __init__( se... | 658 | 1 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_info()... | 658 |
import baseaa
def A ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def A ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecode(_lowerCamelCas... | 658 | 1 |
from __future__ import annotations
import typing
from collections import Counter
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : typing.Counter[int] = Counter()
for base in range(1 , max_perimeter + 1 ):... | 658 |
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
_snake_case = logging.get_logger(__name__)
_snake_case = {
"facebook/data2vec-vision-base-ft... | 658 | 1 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = 0
_lowerCAmelCase : Optional[Any] = len(_lowerCamelCase )
for i in range(n - 1 ):
for j in range(i + 1 ... | 658 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
_snake_case = {
"cola": 2,
"m... | 658 | 1 |
from __future__ import annotations
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , ):
'''simple docstring'''
_lowerCAmelCase : List[str] = len(_lowerCamelC... | 658 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
_snake_case = "\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Method for Automatic Evalua... | 658 | 1 |
def A ( _lowerCamelCase = 1_000_000 ):
'''simple docstring'''
_lowerCAmelCase : Any = 1
_lowerCAmelCase : Optional[Any] = 1
_lowerCAmelCase : List[str] = {1: 1}
for inputa in range(2 , ... | 658 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def A ( _lowerCamelCase , _lowerCamelCase=False ):
'''simple docstring'''
_lowerCAmelCase : Dict = OmegaConf.load(_lowerC... | 658 | 1 |
from collections import deque
from math import floor
from random import random
from time import time
class UpperCAmelCase_ :
def __init__( self):
'''simple docstring'''
_lowerCAmelCase : Tuple = {}
def snake_case__ ... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}
class UpperCAmelCase_ ( a):
l... | 658 | 1 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len(_lowerCamelCase )
for i in range(1 , _lowerCamelCase ):
_lowerCAmelCase : List[Any] = collection[i]
... | 658 |
from __future__ import annotations
def A ( _lowerCamelCase ):
'''simple docstring'''
if not nums:
raise ValueError("List is empty" )
return sum(_lowerCamelCase ) / len(_lowerCamelCase )
if __name__ == "__main__":
import ... | 658 | 1 |
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
_snake_case = numpy.array([0, 0])
_snake_case = numpy.array([0.5, 0.8660254])
_snake_case = numpy.array([1, 0])
_snake_case = [VECTOR_1, VECTOR_2, VECTOR_3, VECT... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
if length <= 0 or not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(_lowerCamelCase... | 658 | 1 |
import string
def A ( _lowerCamelCase ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
_lowerCAmelCase : str = ""
for symbol in message:
if symbol in string.asc... | 658 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def A ( _lowerCamelCase ):
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def ... | 658 | 1 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Any = [0] * len(_lowerCamelCase )
_lowerCAmelCase : Optional[int] = []
_lowerCAmelCase : Optional[Any] = []
_lowerCAmel... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[str] = BeautifulSoup(requests.get(_lowerCamelCase , params=_lowerCamelCase ).content ... | 658 | 1 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInput,... | 658 |
def A ( _lowerCamelCase = 1_000_000 ):
'''simple docstring'''
_lowerCAmelCase : Any = 1
_lowerCAmelCase : Optional[Any] = 1
_lowerCAmelCase : List[str] = {1: 1}
for inputa in range(2 , ... | 658 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05) = }''')
| 658 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
_snake_case = "https://openaipublic.azureedg... | 658 | 1 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Tu... | 658 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple... | 658 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_snake_case = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"GroupViTOnnxConfig",
"GroupViTTe... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len(_lowerCamelCase )
for i in range(1 , _lowerCamelCase ):
_lowerCAmelCase : List[Any] = collection[i]
... | 658 | 1 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake_case = logging.get_logger(__name__)
_snake_case = {
"microsoft/focalnet-tiny": "https://huggingface.co/microsof... | 658 | 1 |
import cva
import numpy as np
class UpperCAmelCase_ :
def __init__( self, __a, __a):
'''simple docstring'''
if k in (0.04, 0.06):
_lowerCAmelCase : Any = k
_lowerCAmelCase : Tuple ... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
def count_of_possible_combinations(_lowerCamelCase ) -> int:
if target < 0:
return 0
if target == 0:
... | 658 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_snake_case = {"configuration_yolos": ["YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP", "YolosConfig", "YolosOnnxConfig"]}
try:
if not is_vision_available():
ra... | 658 |
import string
def A ( _lowerCamelCase ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
_lowerCAmelCase : str = ""
for symbol in message:
if symbol in string.asc... | 658 | 1 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common i... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
_lowerCAmelCase : str = BeautifulSoup(requests.get(_lowerCamelCase ).text , "html.parser"... | 658 | 1 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRetr... | 658 |
from __future__ import annotations
from collections.abc import MutableSequence
class UpperCAmelCase_ :
def __init__( self, __a, __a):
'''simple docstring'''
if len(__a) != degree + 1:
raise ValueError(
... | 658 | 1 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerC... | 658 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
"xlnet-large-cased": "https://huggingface.co/xlnet... | 658 | 1 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
_snake_case = logging.get_logger(__name__)
def A ( _lowerCamelCase , _l... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05) = }''')
| 658 | 1 |
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor
if is_flax_availab... | 658 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( a):
lowerCamelCase__ = 'upernet'
def __init__( se... | 658 | 1 |
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
_snake_case = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
"text-classification",
"language-... | 658 |
import baseaa
def A ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def A ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecode(_lowerCamelCas... | 658 | 1 |
_snake_case = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0",
"huggingface-hub": "huggingface-hub>=0... | 658 |
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
_snake_case = logging.get_logger(__name__)
_snake_case = {
"facebook/data2vec-vision-base-ft... | 658 | 1 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self, __a, __a, __a, __a, __a, __a=0.2, __a=0.2):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 658 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
_snake_case = {
"cola": 2,
"m... | 658 | 1 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoConfig,
A... | 658 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
_snake_case = "\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Method for Automatic Evalua... | 658 | 1 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"nielsr/canine-s": 2048,
}
# Unicode defines 1,114,112 total “codepoints”
_snake_case = 111_4112
... | 658 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def A ( _lowerCamelCase , _lowerCamelCase=False ):
'''simple docstring'''
_lowerCAmelCase : Dict = OmegaConf.load(_lowerC... | 658 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Any = [0 for i in range(r + 1 )]
# nc0 = 1
_lowerCAmelCase : Any = 1
for i in range(1 , n + 1 ):
... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}
class UpperCAmelCase_ ( a):
l... | 658 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impo... | 658 |
from __future__ import annotations
def A ( _lowerCamelCase ):
'''simple docstring'''
if not nums:
raise ValueError("List is empty" )
return sum(_lowerCamelCase ) / len(_lowerCamelCase )
if __name__ == "__main__":
import ... | 658 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( a):
lowerCamelCase__ = 'upernet'
def __init__( se... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
if length <= 0 or not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(_lowerCamelCase... | 658 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_snake_case = {"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNo... | 658 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def A ( _lowerCamelCase ):
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def ... | 658 | 1 |
import math
def A ( _lowerCamelCase , _lowerCamelCase = 0 , _lowerCamelCase = 0 ):
'''simple docstring'''
_lowerCAmelCase : str = end or len(_lowerCamelCase )
for i in range(_lowerCamelCase , _lowerCamelCas... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[str] = BeautifulSoup(requests.get(_lowerCamelCase , params=_lowerCamelCase ).content ... | 658 | 1 |
_snake_case = frozenset(
[
"prompt",
"height",
"width",
"guidance_scale",
"negative_prompt",
"prompt_embeds",
"negative_prompt_embeds",
"cross_attention_kwargs",
]
)
_snake_case = frozenset(["prompt", "negative_prompt"])
_snake_case... | 658 |
def A ( _lowerCamelCase = 1_000_000 ):
'''simple docstring'''
_lowerCAmelCase : Any = 1
_lowerCAmelCase : Optional[Any] = 1
_lowerCAmelCase : List[str] = {1: 1}
for inputa in range(2 , ... | 658 | 1 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers... | 658 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
_snake_case = "https://openaipublic.azureedg... | 658 | 1 |
from sklearn.metrics import recall_score
import datasets
_snake_case = "\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 and FN is the false negatives.\n"
_... | 658 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"RWKV/rwkv-4-169m-pile": "https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json",
"RWKV/rwkv-4-430m-pile": "https://huggingface.co/RWKV/rwk... | 658 |
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len(_lowerCamelCase )
for i in range(1 , _lowerCamelCase ):
_lowerCAmelCase : List[Any] = collection[i]
... | 658 | 1 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"vocab_file": "vocab.txt",
"merges_file": "bpe.codes",
}
_snak... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake_case = logging.get_logger(__name__)
_snake_case = {
"microsoft/focalnet-tiny": "https://huggingface.co/microsof... | 658 | 1 |
from __future__ import annotations
class UpperCAmelCase_ :
def __init__( self, __a):
'''simple docstring'''
_lowerCAmelCase : str = TypeError(
"Matrices must be formed from a list of zero or more lists containing at... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
def count_of_possible_combinations(_lowerCamelCase ) -> int:
if target < 0:
return 0
if target == 0:
... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
"studio-ousia/luke-large": "https://huggingface.co/stud... | 658 |
import string
def A ( _lowerCamelCase ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
_lowerCAmelCase : str = ""
for symbol in message:
if symbol in string.asc... | 658 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Dict = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
_lowerCAmelCase : str = ... | 658 |
import requests
from bsa import BeautifulSoup
def A ( _lowerCamelCase = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
_lowerCAmelCase : str = BeautifulSoup(requests.get(_lowerCamelCase ).text , "html.parser"... | 658 | 1 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"kakaobrain/align-base": "https://huggingface.co/kakaobrain... | 658 |
from __future__ import annotations
from collections.abc import MutableSequence
class UpperCAmelCase_ :
def __init__( self, __a, __a):
'''simple docstring'''
if len(__a) != degree + 1:
raise ValueError(
... | 658 | 1 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class UpperCAmelCase_ :
lowerCamelCase__ = 42
lowerCamelCase__ ... | 658 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
"xlnet-large-cased": "https://huggingface.co/xlnet... | 658 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(_lowerCamelCase ) )
def A ... | 658 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05) = }''')
| 658 | 1 |
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