code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from d... | 70 |
from __future__ import annotations
class lowerCamelCase_ :
def __init__( self , lowerCamelCase_ , lowerCamelCase_ ) -> int:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase = text, pattern
_UpperCamelCase , _UpperCamelCase =... | 147 | 0 |
'''simple docstring'''
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, ca... | 706 | '''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase : Any = logging.get_logger(__name__)
UpperCa... | 610 | 0 |
from typing import Any
def __UpperCamelCase ( lowercase__ : list , lowercase__ : list , lowercase__ : dict , lowercase__ : dict , lowercase__ : dict , ) -> list:
'''simple docstring'''
_validation(
... | 600 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __UpperCamelCase ( lowercase__ : str ) -> None:
'''simple docstring'''
lowerCAmelCase_ , lowerCAmelCase_ : str = analyze_text(low... | 600 | 1 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE__ : Optional[int] = parse(importlib.metadata.version("torch"))
def A_ ( UpperCAmelCase__ ,... | 509 |
"""simple docstring"""
from math import factorial, pi
def A_ ( UpperCAmelCase__ , UpperCAmelCase__ = 30 ) -> float:
if not isinstance(UpperCAmelCase__ , (int, float) ):
raise ValueError('maclaurin_sin() requires either an int or float for theta' ... | 509 | 1 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowercase = {'UserAgent': UserAgent().random}
def __UpperCamelCase ( a : Any ) ->dict:
s... | 342 |
'''simple docstring'''
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
_lowercase = logging.get_logger(__name__)
class _lowe... | 342 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def UpperCAmelCase ( A : str... | 24 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.... | 24 | 1 |
'''simple docstring'''
def _a (lowercase__ : list , lowercase__ : list , lowercase__ : int ) -> int:
"""simple docstring"""
if len(lowercase__ ) != len(lowercase__ ):
raise ValueError('The length of profit and weight must be same.' ... | 56 |
"""simple docstring"""
def _snake_case ( lowercase__ = 1 , lowercase__ = 1000 ):
_lowerCamelCase : Optional[int] = 1
_lowerCamelCase : List[Any] = 0
for divide_by_number in range(lowercase__ , digit + 1 ):
... | 630 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 184 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 184 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimens... | 236 |
from __future__ import annotations
import os
from typing import Any
import requests
lowerCAmelCase : str = 'https://api.github.com'
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowerCAmelCase : Optional[Any] = BASE_URL + '/user'
# https://github.co... | 511 | 0 |
# 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/LICENSE-2.0
#
# Unless required b... | 718 |
from PIL import Image
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE : List[str] = image.size
_SCREAMING_SNAKE_CASE : Tuple = 0
_SCREAMING_SNAKE_CASE : Dict = image.load()
f... | 381 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : Any = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCode... | 673 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils im... | 673 | 1 |
from __future__ import annotations
import numpy as np
def __a ( __UpperCAmelCase ):
return np.maximum(0 , A__ )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 714 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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 applic... | 148 | 0 |
def _SCREAMING_SNAKE_CASE ( lowercase : int = 10 ):
'''simple docstring'''
if not isinstance(lowercase , lowercase ) or n < 0:
raise ValueError('Invalid input' )
lowerCamelCase_ = 10**n
lowerCamelCase_ = 2_84... | 70 |
"""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/L... | 567 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from... | 40 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase = None ):
if version.parse(hfh.__version__ ).release <... | 40 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
a : str = loggin... | 555 |
"""simple docstring"""
import cva
import numpy as np
class a_ :
def __init__( self : Optional[Any] , __UpperCamelCase : float , __UpperCamelCase : int ) ->Dict:
'''simple docstring'''
if k in (0.0_4, 0.0_6):
... | 555 | 1 |
"""simple docstring"""
__lowerCAmelCase : Any = range(2, 20 + 1)
__lowerCAmelCase : Optional[int] = [10**k for k in range(ks[-1] + 1)]
__lowerCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def __lowerCAmelCase ( ... | 21 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot... | 21 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_com... | 88 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_ : str = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/re... | 692 | 0 |
"""simple docstring"""
a = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
a = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
a = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''Thursday''',
5: '''Friday''',
6: '''Saturday''',
}
def ... | 505 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _snake_case ( _snake_case : List[Any] ) -> Any:
'''simple do... | 505 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def _a (lowercase__ : Sequence[int] | None = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
__snake_case = ... | 56 |
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
from diffusers.utils.testing_utils import enable_full_... | 184 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__UpperCAmelCase : Tuple = {
"configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextCo... | 707 |
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def A__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__) ... | 155 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test... | 50 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ = {
"""configuration_nezha""": ["""NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NezhaConfig"""],
}
try:
if not is_torch_available():... | 678 | 0 |
"""simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
A = logging.get_logger(__name__) # pylint: disable=invalid-name
clas... | 712 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# ... | 101 | 0 |
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_f... | 488 |
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
from transformers.models.b... | 488 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"""uclanlp/visualbert-vqa""": """https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json""",
"""uclanl... | 291 |
def UpperCamelCase ( snake_case__ : str ):
'''simple docstring'''
__snake_case :List[Any] = hex_num.strip()
if not hex_num:
raise ValueError("""No value was passed to the function""" )
__snake_case :str = ... | 291 | 1 |
'''simple docstring'''
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
UpperCAmelCase_ : int = logging.get_logger(... | 24 |
'''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 transform... | 24 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
... | 363 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
_UpperCamelCase = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human an... | 363 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET... | 55 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGEN... | 89 | 0 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import T... | 703 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, ge... | 303 | 0 |
'''simple docstring'''
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
__lowerCAmelCase = (
'''This m... | 466 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__SCREAMING_SNAKE_CASE : str = tuple[int, int]
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ , lowerCamelCase__... | 661 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : int = {
"""configuration_autoformer""": [
"""AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Autoforme... | 146 |
from __future__ import annotations
from math import pow, sqrt
def lowerCAmelCase ( UpperCamelCase__ : float , UpperCamelCase__ : float , UpperCamelCase__ : float ) -> dict[str, float]:
"""simple docstring"""
if (resistance, reactance,... | 146 | 1 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ,lowerCAmelCase_ ):
@register_to_config
def __init__( self : Any , *,
A : ... | 315 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Dict = logging.get_logger(__name__)
_A : Union[str, Any] = {
'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
'studio-ousia/luke... | 315 | 1 |
"""simple docstring"""
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.ge... | 717 |
"""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/blo... | 348 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common imp... | 46 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class snake_case__ :
"""simple docstring"""
_SCREAMING_SNAKE_CASE = field(
... | 478 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
f... | 704 |
"""simple docstring"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def lowerCAmelCase_ ( lowercase_ : ... | 401 | 0 |
def lowerCAmelCase_ ( lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase , ):
__magic_name__ : Optional[Any] =[redshift, radiation_density, matter_density, dark_energy]
if any(p < 0 for p in parameters ):
... | 21 |
UpperCAmelCase_ : Tuple = 0 # The first color of the flag.
UpperCAmelCase_ : Any = 1 # The second color of the flag.
UpperCAmelCase_ : str = 2 # The third color of the flag.
UpperCAmelCase_ : Tuple = (red, white, blue)
def lowerCAmel... | 21 | 1 |
"""simple docstring"""
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 217 | """simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
neste... | 217 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
Vil... | 505 |
"""simple docstring"""
def lowercase (_snake_case ) -> int:
'''simple docstring'''
__UpperCamelCase = len(_snake_case )
__UpperCamelCase = len(matrix[0] )
__UpperCamelCase = min(_snake_case ,_snake_case )
for row in range(_snake_case ... | 505 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase = 1_00_00_00 , __lowerCAmelCase = 10 ) -> int:
'''simple docstring'''
lowercase_ = defaultdict(_UpperCamelCase )
for outer_width in ra... | 715 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models impo... | 100 | 0 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowerCamelCase ... | 677 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
UpperCAmelCase = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and B... | 677 | 1 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
__l... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : str ):
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 21 | 1 |
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowercase_ = numpy.array([0, 0])
lowercase_ = numpy.array([0.5, 0.866_0254])
lowercase_ = numpy.array([1, 0])
lowercase_ = [VE... | 669 |
'''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_... | 369 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase : Optional[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
ex... | 100 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase , __lowerCAmelCase ) -> int:
'''simple docstring'''
while a != 0:
lowercase_ , lowercase_ = b % a, a
return b
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase , __lowerC... | 100 | 1 |
'''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class UpperCAmelCase ( lowercase_):
"""simple docstring"""
lowerCAmelCase_ = """EncodecFeatureExtractor"""
lowe... | 404 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import Tokenize... | 404 | 1 |
"""simple docstring"""
def lowercase__ ( snake_case_ :int = 2_000_000 ):
__UpperCAmelCase = [0 for i in range(n + 1 )]
__UpperCAmelCase = 1
__UpperCAmelCase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
for j in ran... | 700 |
"""simple docstring"""
def lowercase__ ( snake_case_ :List[Any] , snake_case_ :str , snake_case_ :Tuple , snake_case_ :Any , snake_case_ :Union[str, Any] , snake_case_ :List[Any] ):
if index == r:
for j in range(snake_case_ ):
print(data[j] , en... | 397 | 0 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.t... | 63 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : str = logging.get_logger(__name__)
a : Union[str, Any] = {
"microsoft/git-base": "https://huggingface.co/microsoft/git-base... | 63 | 1 |
import numpy as np
import datasets
snake_case__ : int = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt ... | 710 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 0 |
from __future__ import annotations
from typing import Any
def __A ( _lowercase ):
'''simple docstring'''
create_state_space_tree(_lowercase , [] , 0 )
def __A ( _lowercase , _lowercase , _lowercase ):
'''simple d... | 484 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ ... | 381 | 0 |
import math
import tensorflow as tf
from packaging import version
def lowerCamelCase( a__):
_SCREAMING_SNAKE_CASE =tf.convert_to_tensor(lowerCAmelCase_)
_SCREAMING_SNAKE_CASE =0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0) ,x.dtype)))
return x * cdf
def lowerC... | 703 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_to... | 191 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ ... | 560 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/r... | 560 | 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 lowerCAmelCase_ :
lowerCamelCase_ = 42
lowerCamelCase_ = None... | 373 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
from ... | 373 | 1 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if imp... | 247 |
"""simple docstring"""
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def UpperCAmelCase ( snake_case : int , snake_case : int , snake_case : float = 1 / sqrt(2 ) ):
_lowerCAmelCase:Union[str, Any] ... | 227 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : str = logging.get_logger(__name__)
UpperCamelCase__ : Optional[Any] = {
'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/con... | 715 | '''simple docstring'''
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def __UpperCamelCase( _A : str ):
'''simple docstring'''
return 1 / (1 + np.exp(-z ))... | 496 | 0 |
def __UpperCAmelCase ( lowerCamelCase_ : str ) -> str:
"""simple docstring"""
return " ".join(
''.join(word[::-1] ) if len(snake_case__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()... | 105 | import tensorflow as tf
from ...tf_utils import shape_list
class a ( tf.keras.layers.Layer ):
"""simple docstring"""
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , ... | 401 | 0 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
__SCREAMING_SNAKE_CASE : Tuple =version.parse(importlib_metadata.version('''nltk'''))
if NLTK_VERSION >= version.Version('''3.6.4'''):
from nltk import wo... | 72 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...f... | 72 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging... | 96 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrateg... | 586 | 0 |
'''simple docstring'''
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : Any = ... | 47 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 47 | 1 |
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowerCamelCase : Optional[Any] = numpy.array([0, 0])
lowerCamelCase : Optional[int] = numpy.array([0.5, 0.866_0254])
lowe... | 70 |
import argparse
import json
import subprocess
def _SCREAMING_SNAKE_CASE ( lowercase : Dict , lowercase : List[str] ):
'''simple docstring'''
lowerCamelCase_ = []
lowerCamelCase_ = (
f"""curl -H \"Accept:... | 70 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_determinism,
load_numpy,
... | 703 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def A__ ( __lowerCamelCase = "laptop" ):
SCREAMING_SNAKE_CASE_ = F'''https://www.amazon.in/laptop/s?k={product}'''
SCREAMING_SNAKE_CASE_ = {
'''User-Agent''': '''Mozilla/5.0 (X11;... | 597 | 0 |
def lowerCAmelCase_ ( lowerCamelCase , lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 21 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowerCAmelCase_ ( lowerCamelCase ):
# A local function to see if a dot lands in the circle.
def is_in_circle(lowerCamelCase , lowerCamelCase ) -> bool:... | 21 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import ... | 712 |
"""simple docstring"""
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase ):
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
... | 549 | 0 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class snake_case_ ( lowerCAmelCase ):
__lowerCamelCase : List[str] = (EulerDiscreteScheduler,)
__lowerCamelCase : ... | 345 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching bet... | 605 | 0 |
'''simple docstring'''
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from ... | 707 |
'''simple docstring'''
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( a_ ):
SCREAMING_SNAKE_CASE : List[Any] = (IPNDMScheduler,)
SCREAMING_SNAKE_CASE : Optional[Any] = (('''num... | 514 | 0 |
"""simple docstring"""
from typing import List
import numpy as np
def __lowercase ( snake_case_ : dict ) ->int:
'''simple docstring'''
__A : Optional[int] = {key: len(snake_case_ ) for key, value in gen_kwargs.items() if isinstance(snake_case_ ,snake... | 177 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noq... | 177 | 1 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime ... | 366 | """simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow h... | 366 | 1 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( __snake_case : Dict ):
if not head:
return True
# split the list to two parts
_A , _A = head.next, head
while fast and fast.next:
_A = fast.next.next
_A = slow.next
... | 107 |
'''simple docstring'''
import os
lowercase : Tuple = {'I': 1, 'V': 5, 'X': 1_0, 'L': 5_0, 'C': 1_0_0, 'D': 5_0_0, 'M': 1_0_0_0}
def __a ( A__ ) -> int:
lowerCAmelCase = 0
lowerCAmelCase = 0
while index < len(A__ ) - 1:
lowerC... | 649 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowercase : Union[str, Any] =logging.get_logger(__name__)... | 708 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : int =logging.get_logger(__name__)
_lowercase : Dict ={
'''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/config.json''',
# See ... | 661 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
__magic_name__ : Optional[Any] = TypeVar("""T""")
class lowercase__ ( Generic[T] ):
"""simple docstring"""
def __init__( self , ... | 102 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_ = {
"""configuration_table_transformer""": [
"""TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""TableTransformerConfig""",
"""TableTransfor... | 413 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__lowerCamelCase :Optional[Any] = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
impo... | 702 |
"""simple docstring"""
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_c... | 42 | 0 |
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_available():
from PIL import Image
from ..image_u... | 345 |
import unittest
from transformers import DonutProcessor
_a : Optional[int] = 'naver-clova-ix/donut-base'
class a_ ( unittest.TestCase ):
def lowerCAmelCase( self : Tuple ):
"""simple docstring"""
snake_case : Option... | 598 | 0 |
import warnings
warnings.warn(
'''memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '''
'''`from accelerate import find_executable_batch_size` to avoid this warning.''',
FutureWarning,
)
| 189 |
def __lowerCAmelCase ( snake_case : int = 1000000 ) -> int:
__lowerCamelCase: Union[str, Any] = set(range(3 , snake_case , 2 ) )
primes.add(2 )
for p in range(3 , snake_case , 2 ):
if p not in primes:
continue
... | 189 | 1 |
"""simple docstring"""
__lowerCAmelCase : List[Any] =[
"""Audio""",
"""Array2D""",
"""Array3D""",
"""Array4D""",
"""Array5D""",
"""ClassLabel""",
"""Features""",
"""Sequence""",
"""Value""",
"""Image""",
"""Translation""",
"""Translatio... | 359 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : int =logging.get_logger(__name__)
__lowerCAmelCase : Optional[Any] ={
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base... | 359 | 1 |
'''simple docstring'''
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatur... | 713 |
'''simple docstring'''
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_snake_case : Union[str, Any] = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_vers... | 493 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
i... | 649 |
'''simple docstring'''
def __a ( A__ , A__ ) -> int:
return int((input_a, input_a).count(0 ) == 0 )
def __a ( ) -> None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 ... | 649 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase : Any = TypeVar('T')
UpperCAmelCase : str = TypeVar('U')
class lowerCamelCase (Generic[T, U] ):
def __init__( self ... | 705 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCAmelCase : str = logging.getLogger(__name__)
UpperCAmelCas... | 47 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
lowerCAmelCase__ = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
lowerCAmelCase__ = [file for file in filepaths if file != file... | 514 |
from PIL import Image
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Image , SCREAMING_SNAKE_CASE_: int ) -> Image:
'''simple docstring'''
A__ = (2_5_9 * (level + 2_5_5)) / (2_5_5 * (2_5_9 - level))
def contrast(SCREAMING_SNAKE_CASE_: i... | 514 | 1 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : str ) -> list[int]:
return [ord(UpperCAmelCase_ ) - 9_6 for elem in plain]
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : list[int] ) -> str:
return "".join(chr(elem + 9_6 ... | 431 |
import gc
import unittest
from transformers import CTRLConfig, 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 Mode... | 431 | 1 |
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
snake_case__ : Union[str, Any] = False
snake_case__ : int = True
snake_case__ : List[str] = ... | 392 |
def lowercase ( _lowerCAmelCase ):
UpperCAmelCase__ = len(_lowerCAmelCase )
while cur > 1:
# Find the maximum number in arr
UpperCAmelCase__ = arr.index(max(arr[0:cur] ) )
# Reverse from 0 to mi
UpperCAmelCase__ = arr[mi::-1] + arr[mi + 1 : len(_... | 392 | 1 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
MusicgenProcessor,... | 717 |
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
__snake_case :List[str] = re.compile(r'''^(?P<major>\d+)''' r'''\.(?P<minor>\d+)''' r'''\.(?P<patch>\d+)$''')
@total_ordering
@dataclass
class _A :
... | 60 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__SCREAMING_SNAKE_CASE = {'processing_wav2vec2_with_lm': ['Wav2Vec2ProcessorWithLM']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
__SCREAMING_SNAKE_C... | 688 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__SCREAMING_SNAKE_CASE = logging.getLogger(__name__)
class lowerCAmelCase__ :
"""simple... | 688 | 1 |
from math import isqrt, loga
def snake_case__ ( UpperCAmelCase : int ):
lowerCAmelCase__ :Optional[int] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , Up... | 111 |
def snake_case__ ( UpperCAmelCase : float ):
if edge <= 0 or not isinstance(UpperCAmelCase , UpperCAmelCase ):
raise ValueError("Length must be a positive." )
return 3 * ((2_5 + 1_0 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def snake_case__ ... | 111 | 1 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
_UpperCamelCase =... | 341 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="""%(message)s""")
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ ) -> np.ndarray:
return input_array.reshape((input_array.size, 1) )
def ... | 652 | 0 |
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 import DUMMY_UNKNOWN_IDE... | 588 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor impo... | 588 | 1 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase__ ( metaclass=__magic_name__ ):
'''simple docstring'''
lowercase_ = ["""torch"""]
def __init__( self , *lowercase__ , **lowercase__ ):
'''simple docstrin... | 184 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_lowerCamelCase : List[Any] = logging.getLogger(__name__)
class lowerCAmelCase__ ( __magic_name__ ):
''... | 184 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_visio... | 50 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase__( metaclass=lowerCAmelCase ):
__magic_name__ : List[str] = ["note_seq"]
def __init__( self : Any , *lowerCAmelCase : List[str] , **lowerCAmelCase : int... | 50 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
"configuration_perceiver": ["PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP", "PerceiverConfig", "Perce... | 307 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
... | 249 | 0 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCamelCase_ : Dict = HfApi()
lowerCamelCase_ : str = {}
# fmt: off
lowerCamelCase_ : Tuple = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.... | 710 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_an... | 345 | 0 |
"""simple docstring"""
import os
def A_ ( snake_case_ : Any ):
'''simple docstring'''
UpperCamelCase : str = len(grid[0] )
UpperCamelCase : int = len(snake_case_ )
UpperCamelCase : Optional[int] = 0
UpperCamel... | 499 |
"""simple docstring"""
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGE... | 499 | 1 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils imp... | 426 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization i... | 426 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_snake_case = '''https://www.indeed.co.in/jobs?q=mobile+app+development&l='''
def __snake_case ( SCREAMING_SNAKE_CASE: s... | 580 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimen... | 61 | 0 |
def UpperCamelCase( lowercase_ , lowercase_ ) -> Tuple:
'''simple docstring'''
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def UpperCamelCase( lowercase_ , lowercase_=0 ) -> str:
'''simple docstring'''
... | 721 |
# 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/LICENSE-2.0
#
# Unless required by ap... | 161 | 0 |
'''simple docstring'''
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
... | 90 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class UpperCAmelCase__ ( unittest.TestCase ):
"""simple docstring"""
def lowercase... | 493 | 0 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
if isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise TypeError('\'float\' object cannot be interpreted as an integer' )
if isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise TypeError('\'str... | 705 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
stooge(SCREAMING_SNAKE_CASE , 0 , len(SCREAMING_SNAKE_CASE ) - 1 )
return arr
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -... | 311 | 0 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
__SCREAMING_SNAKE_CASE ={
"""facebook/maskformer-swin-base-ade"""... | 234 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTt... | 234 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, Attn... | 254 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
... | 254 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class lowercase__ :
'''simple docstring'''
_snake_case = 42
_snake_case = None
_snake_case = None
... | 212 |
'''simple docstring'''
# Copyright 2022 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
#
# Unl... | 683 | 0 |
import math
def __lowerCamelCase ( __a : int ) -> list[int]:
_lowercase =[]
_lowercase =2
_lowercase =int(math.sqrt(__a ) ) # Size of every segment
_lowercase =[True] * (end + 1)
_lowercase =[]
while start <= end:
if temp[start] is True:
in_prime.appe... | 594 | import json
from typing import TYPE_CHECKING, 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_blenderbot import Blende... | 594 | 1 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
fro... | 207 |
'''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... | 207 | 1 |
import qiskit
def lowerCamelCase_ ( lowerCamelCase__ = 2 ):
lowerCamelCase_ = qubits
# Using Aer's simulator
lowerCamelCase_ = qiskit.Aer.get_backend("aer_simulator" )
# Creating a Quantum Circuit acting on the q register
lowerCamelCase_ =... | 715 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import ... | 313 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase : Optional[Any] =logging.get_logger(__name__)
_lowercase : Dict ={
'''roberta-base''': '''htt... | 305 | import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import ... | 305 | 1 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase = 1_00 ) -> int:
'''simple docstring'''
lowercase_ = set()
lowercase_ = 0
lowercase_ = n + 1 # maximum limit
for a in range(2 , __lowerCAmelCase ):
for ... | 100 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .... | 100 | 1 |
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