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 os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos.json'],
['datase... | 410 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, slow
... | 410 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import Counter
from random import random
class a :
"""simple docstring"""
def __init__( self ) -> Any:
_UpperCAmelCase = {}
def __A ( self ,... | 717 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
fro... | 579 | 0 |
A_ : Optional[int] = [0, 2, 4, 6, 8]
A_ : List[Any] = [1, 3, 5, 7, 9]
def __a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> int:
'''simple docstring'''
if remaining_length == 0:... | 303 |
from __future__ import annotations
def __a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> list[str]:
'''simple docstring'''
if nth_term == "":
return [""]
__UpperCAmelCase = int(SCREAMING_SNAKE_CASE )
__UpperCAmelCase ... | 303 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import LearnedC... | 205 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
snake_case_ : Optional[Any] =Lock()
def UpperCAmelCase ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase_... | 205 | 1 |
def a__ ( __UpperCamelCase , __UpperCamelCase ):
while second != 0:
SCREAMING_SNAKE_CASE_ = first & second
first ^= second
SCREAMING_SNAKE_CASE_ = c << 1
return first
if __name__ == "__main__":
import doctest
doctest.testmod()
A : ... | 140 | def a__ ( __UpperCamelCase ):
if length <= 0 or not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(__UpperCamelCase )]
if __name__ == "__main__":
print(hexagonal_num... | 140 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_ind... | 298 |
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
from transformers im... | 298 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any]... | 679 |
'''simple docstring'''
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class UpperCamelCase__ ( lowercase__ ):
"""simple docstring"""
def A_ ( self , snake_case ):
'''simple docstring'''
with open... | 679 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a= {
'''configuration_owlvit''': [
'''OWLVIT_PRE... | 287 | '''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
a= logging.get_logger(__name__)
class __lowercase ( _... | 287 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase ( _snake_case ,_snake_case = None ,_snake_case = None ):
if start is None:
UpperCAmelCase__ : List[str] = 0
if end is None:
UpperCAmelCase__ : str = len(_sna... | 110 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 106 | 0 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def __lowercase ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ) -> list[float]:
'''simple docstring'''
__lowercase , __lowercase =... | 711 | from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class snake_case ( __snake_case ):
"""simple docstring"""
... | 576 | 0 |
"""simple docstring"""
import argparse
import json
import subprocess
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = []
__lowerCAmelCase = (
f"curl -H \"Accept: application/vnd.github+... | 636 |
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.generation import (
MaxLengthCriteria,
Ma... | 678 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"Salesforce/blip-vqa-base": "https://huggingface.co/Salesforce/b... | 717 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class lowerCamelCase__ ( SCREAMIN... | 255 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, Te... | 359 | """simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( lowerCAmelCase__ :dict , lowerCAmelCase__ :str ) -> set[str]:
'''simple docstring'''
lowercase , lowercase = set(lowerCAmelCase__ ), [start]
... | 359 | 1 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __UpperCAmelCase ( _UpperCAmelCase : Optional[int] , _UpperCAmelCase : Tuple , _UpperCAmelCase : Any ) -> str:
__snake_case = 0
if start... | 680 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
a : str = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'''],... | 680 | 1 |
def lowerCamelCase__ ( _lowercase ):
'''simple docstring'''
UpperCAmelCase_ : List[str] = len(_lowercase )
for _ in range(_lowercase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
UpperCAmelCase_, ... | 30 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_num... | 499 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
"Salesforce/blip-vqa-base": "https://huggingface.co/Salesforce/blip-vqa-base/res... | 705 |
import inspect
import unittest
from transformers import YolosConfig
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 import ConfigTester
from ... | 129 | 0 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArgume... | 79 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_A = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeBertConf... | 159 | 0 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import r... | 554 |
"""simple docstring"""
from math import ceil
def __lowerCamelCase ( lowerCAmelCase__ ,lowerCAmelCase__ ):
A__ = list(range(0 ,lowerCAmelCase__ ) )
A__ = [item for sublist in list(device_map.values() ) for item in su... | 554 | 1 |
from ..utils import DummyObject, requires_backends
class __a( metaclass=_a ):
"""simple docstring"""
lowerCAmelCase = ['''torch''', '''torchsde''']
def __init__( self ,*_SCREAMING_SNAKE_CASE ,**_SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
requires_bac... | 30 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...t... | 621 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if i... | 43 | '''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : str , _UpperCamelCase : list[str] ):
'''simple docstring'''
UpperCAmelCase_ = ''''''
for word_or_phrase in separated:
if not isinstance(_UpperCamelCase , _UpperCamelCase ... | 43 | 1 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
__A = logging.getLogger()
@unittest.skip('Temporarily disable the doc tests.' )
@require_torch
@r... | 68 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr... | 596 | 0 |
from __future__ import annotations
def _UpperCAmelCase ( a : str , a : list[str] | None = None ):
snake_case__ = word_bank or []
# create a table
snake_case__ = len(a ) + 1
snake_case__ = []
for _ in range(a ):
table.appe... | 99 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data import DataLoader, ... | 99 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
re... | 595 |
"""simple docstring"""
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case_ : Union[st... | 595 | 1 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
SCREAMING_SNAKE_CASE_ = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership fu... | 116 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
# See all PEG... | 116 | 1 |
from __future__ import annotations
from math import pi, sqrt
def __UpperCamelCase (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> tuple:
if inductance <= 0:
raise ValueError('Inductance cannot be 0 or negative' )
elif capacitance <= 0:
raise... | 235 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __UpperCamelCase () -> Optional[Any]:
lowercase__ = {
'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'],
... | 235 | 1 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
SCREAMING_SNAKE_CASE_ = "\\n\n"
SCREAMING_SNAKE_CASE_ = "\nPerplexity (PPL) is one of the m... | 712 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torc... | 201 | 0 |
from typing import Any
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , ) -> list:
_validation(
UpperCAmelCase__ , UpperCAmelCase__ , UpperC... | 57 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase ( lowerCamelCase_ :int = 4 ):
'''simple docstring'''
snake_case_ : Union[str, Any] = abs(__snake_case ) or 4
return [[1 + x + y * row_size for x in range(__snake_case )] for y in ra... | 713 |
'''simple docstring'''
def UpperCAmelCase ( lowerCamelCase_ :str ):
'''simple docstring'''
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase_ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
... | 267 | 0 |
from pathlib import Path
import numpy as np
from PIL import Image
def A__ ( SCREAMING_SNAKE_CASE_ : np.ndarray ) -> np.ndarray:
"""simple docstring"""
_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = rgb[:, :, 0], rgb[:, :, 1],... | 32 |
def lowerCamelCase__ ( _a):
if not isinstance(_a , _a):
SCREAMING_SNAKE_CASE : Tuple = f"Input value of [number={number}] must be an integer"
raise TypeError(_a)
if number < 0:
return False
SCREAMING_SNAKE_CASE : Union[str, Any] = number * number
while number >... | 25 | 0 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def __UpperCamelCase ( snake_case__ ):
return np.dot(a_ , a_ )
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__(self , ... | 705 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
_lowerCAmelCase = ... | 480 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Tuple = {
'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}
try:
if not is_torch_available():
... | 98 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a ( UpperCAmelCase__ ):
UpperCamelCase : Any = 'Speech2TextFeatureExtractor'
UpperCamelCase : Optional[Any] = 'S... | 409 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
a : List[str] = {
'''configuration_spe... | 713 |
'''simple docstring'''
import os
from math import logaa
def __UpperCAmelCase ( _UpperCAmelCase : str = "base_exp.txt" ) -> int:
__snake_case = 0
__snake_case = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(_UpperCAmelCase ) , _UpperCAmelCase )... | 680 | 0 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class snake_case__ ( unittest.TestCase):
def A ( self : int ) -> Optional[int]:
debug_launcher(... | 541 |
'''simple docstring'''
import collections
import os
import re
from pathlib import Path
_UpperCamelCase : Optional[int] = 'src/transformers'
# Matches is_xxx_available()
_UpperCamelCase : int = re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {x... | 541 | 1 |
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 = logging.get_logger(__name__)
__UpperCamelCase = {'vocab_fi... | 185 |
from typing import Any
class lowerCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case ):
'''simple docstring'''
UpperCamelCase__ = data
UpperCamelCase__ = None
class lowerCamelCase__ :
... | 185 | 1 |
"""simple docstring"""
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import Padd... | 642 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __lowerCamelCase :
"""simple docstring"""
a = 42
a = None
a = None
A : Optional[Any] = na... | 128 | 0 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def lowerCamelCase ( UpperCAmelCase__ : int ) -> str:
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError("""Undefined for non-integers""" ... | 717 | '''simple docstring'''
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def lowerCamelCase ( UpperCAmelCase__ : Union[str, Any] , UpperCAmelCase__ : in... | 30 | 0 |
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
__lowerCAmelCase =models.Sequential()
# Step 1 - Convolution... | 333 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__lowerCAmelCase =pytest.mark.integration
@pytest.mark.parametrize("path" , ["paws", "csv"] )
def ... | 333 | 1 |
'''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 | '''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformer... | 496 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCamelCase : Optional[Any] = {
"""configuration_pix2struct""": [
"""PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Pix2StructConfi... | 87 |
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> dict:
"""simple docstring"""
A__ = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(lowercase_ ).json()
def... | 87 | 1 |
from string import ascii_uppercase
lowercase__ :List[Any] = {str(ord(c) - 55): c for c in ascii_uppercase}
def UpperCamelCase ( lowerCAmelCase__ , lowerCAmelCase__ ):
'''simple docstring'''
if isinstance(snake_case_ , snake_case_ ):
raise TypeError('''int() c... | 703 |
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"The `inpainting.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionInpaintPipeline` instead."
)
| 633 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class A_ :
def __init__( self : int , snake_case_ : int , snake_case_ : int , snake_case_ : float = 0 ):
_UpperCAmelCase = row, c... | 236 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 125 | 0 |
import os
def lowerCamelCase__ ():
_SCREAMING_SNAKE_CASE : Any = os.path.dirname(os.path.realpath(__lowerCamelCase ) )
_SCREAMING_SNAKE_CASE : Tuple = os.path.join(__lowerCamelCase, "triangle.txt" )
with open(__lowerCamelCase ) as f:
... | 381 |
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (
BarkCoarseConfig,
... | 381 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_to... | 227 |
"""simple docstring"""
import argparse
import datetime
def UpperCAmelCase ( snake_case : str ):
_lowerCAmelCase:Dict = {
'''0''': '''Sunday''',
'''1''': '''Monday''',
'''2''': '''Tuesday''',
'''3''': '''Wednesday''',
'''4''': ''... | 227 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ = {"""configuration_mbart""... | 275 | """simple docstring"""
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __UpperCAmelCase ( lower... | 275 | 1 |
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_common import BackboneT... | 32 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __lowerCAmelCase ( unittest.TestCase , lowercase ):
"""simple docstring"""
def _UpperCAmelCase ( self : List[str] ):
... | 452 | 0 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
_A = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Ka... | 710 |
"""simple docstring"""
from math import isqrt
def lowercase_ ( __UpperCAmelCase ) -> bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(__UpperCAmelCase ) + 1 ) )
def lowercase_ ( __UpperCAmelCase = 10**6 ) -> int:
lowerCAmelCase__ ... | 507 | 0 |
'''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class a_ :
pass
| 263 |
'''simple docstring'''
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
lowercase__ ... | 263 | 1 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def a ( snake_case__: Optional[int... | 409 |
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 ...tes... | 409 | 1 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
Fla... | 105 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
UpperCamelCase__ : List[Any] = pytest.mark.integration
@pytest.mark.parametrize('path' , ... | 105 | 1 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__lowerCamelCase : Any = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Bur... | 701 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__lowerCamelCase : Union[str, Any] = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose ... | 418 | 0 |
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.utils import WEIGH... | 214 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
lowerCAmelCase : int = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( __a ):
'''simple docstring'''
def __init__( self : Tuple , *low... | 214 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : int =logging.get_logger(__name__)
lowerCAmelCase : str ={
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr-ctx_encoder-single-... | 693 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _UpperCAmelCase ( ):
'''simple docstring'''
with offline(O... | 693 | 1 |
__UpperCAmelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__UpperCAmelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__UpperCAmelCase = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''Thursday''',
5: '''Friday''',
6: '''Saturday''',
}
def ... | 40 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowerConfi... | 296 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : Any = {
"configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
"tokeniza... | 18 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqCon... | 18 | 1 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
requ... | 638 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : Any = False
while is_sorted is False: # Until all the indices are traversed keep looping
A_ : List[Any] = True
for i in range(0 , len(lowerCamelCase__ ) - 1 , 2 ): # ... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
# See all PEGASUS models at https://huggingf... | 669 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class A_ ( __UpperCamelCase ):
'''simpl... | 669 | 1 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Effici... | 152 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 152 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowercase_ = 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
# T... | 11 |
from __future__ import annotations
def __lowerCAmelCase ( A , A ):
UpperCAmelCase_ = []
UpperCAmelCase_ = []
UpperCAmelCase_ = 0
UpperCAmelCase_ = sum(A )
create_state_space_tree(A , A , A , A , ... | 162 | 0 |
'''simple docstring'''
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def __A ( a_ : Union[str, Any] ,a_ : int ):
# ===== initialization =====
lowerCAmelCase : Optional[i... | 551 |
'''simple docstring'''
from __future__ import annotations
lowerCAmelCase = []
def __A ( a_ : list[list[int]] ,a_ : int ,a_ : int ):
for i in range(len(a_ ) ):
if board[row][i] == 1:
return False
for i in range(len(a_ ) ):
if b... | 551 | 1 |
"""simple docstring"""
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class a :
"""simple docstring"""
@property... | 426 |
import unittest
from knapsack import greedy_knapsack as kp
class _A ( unittest.TestCase ):
def __a ( self : List[Any] ) -> Optional[int]:
"""simple docstring"""
lowercase : Dict = [10, 20, 30, 40, ... | 217 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase: Dict ={
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Longf... | 706 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import ... | 585 | 0 |
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 REGEX_COMMIT_HASH
from huggingface_h... | 321 |
"""simple docstring"""
from __future__ import annotations
def __UpperCAmelCase ( __UpperCamelCase = 4 ):
__lowercase : Dict = abs(__UpperCamelCase ) or 4
return [[1 + x + y * row_size for x in range(__UpperCamelCase )] for y in range(__UpperCamelCase )]... | 76 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TF... | 707 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
snake_case__ : List[Any] = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str, requi... | 171 | 0 |
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
__a: Dict = logging.get_logger(__name__)
__a: Optional[int] = {
... | 108 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 601 | 0 |
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 = logging.get_logger(__name... | 701 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
... | 383 | 0 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
__SCREAMING_SNAKE_CASE : Union[str, Any] =logging.get_logger(__name__) # pylint: disable=invalid-name
... | 428 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slo... | 428 | 1 |
from jiwer import compute_measures
import datasets
a_ = """\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved evaluation measures for connected speech... | 286 | from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=snake_case ):
"""simple docstring"""
lowerCAmelCase__ : List[str] = ['transformers', 'torch', 'note_seq']
def __init__( self: List[str] , *__lowerCAmelCase: Optional[int] , **... | 286 | 1 |
"""simple docstring"""
from statistics import mean, stdev
def __snake_case ( SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : int = 3 ) -> list:
'''simple docstring'''
_UpperCAmelCase : str = min(SCREAMING_SNAKE_CASE__ )
... | 289 |
"""simple docstring"""
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,
MusicgenForConditionalGenerat... | 289 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
'facebook/data2vec-text-base': 'http... | 240 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = '▁'
_UpperCAme... | 240 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import random
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : Dict , UpperCAmelCase : int | None = None ) -> Union[str, Any]:
'''simple docstring'''
lowercase... | 94 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 649 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..... | 576 | import math
def __lowercase ( _UpperCAmelCase ) -> str:
'''simple docstring'''
__lowercase = 0
__lowercase = 0
while num > 0:
__lowercase = num % 8
__lowercase = octal + (remainder * math.floor(math.pow(10 , _UpperCAmelCase ) ))
counter += 1
__lowerca... | 576 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
BertTokenizerFast,
Bli... | 540 |
import math
def _UpperCAmelCase ( a__ = 1_0_0):
'''simple docstring'''
a_ : List[str] = sum(i * i for i in range(1 , n + 1))
a_ : Optional[Any] = int(math.pow(sum(range(1 , n + 1)) , 2))
return square_of_sum - sum_of_squares
if __name__ == "__main_... | 540 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = '▁'
UpperCamelCase_ = ... | 142 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( snake_case__ , snake_case__ , snake_case__ , snake_case__ ) -> list:
__UpperCAmelCase =[]
__UpperCAmelCase , __UpperCAmelCase =input_list[low:mid], input_list[mid : high + 1]
whil... | 142 | 1 |
def lowerCamelCase__ ( _lowercase , _lowercase ):
'''simple docstring'''
UpperCAmelCase_ : Dict = [0 for i in range(r + 1 )]
# nc0 = 1
UpperCAmelCase_ : int = 1
for i in range(1 , n + 1 ):
# to compute current row from previous row.
... | 30 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | 318 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _SCREAMING_SNAKE_CASE ( lowerCAmelCase__):
_UpperCamelCase:List[Any] = "ClapFeatureExtractor"
_UpperCamelCase:List[Any] = ("RobertaTokenizer", "RobertaTokenizerFast")
def __i... | 75 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 75 | 1 |
class a_ :
def __init__( self , SCREAMING_SNAKE_CASE = "" , SCREAMING_SNAKE_CASE = False ) -> None:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = {}
# A node will be a leaf if the tree contains its word
SCREAMING_SNAKE_CASE_ ... | 205 |
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 205 | 1 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase_ : int... | 711 |
'''simple docstring'''
import warnings
from ..trainer import Trainer
from ..utils import logging
UpperCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
class UpperCAmelCase__ ( A ):
def __init__( self : int,__A : Any=None,**__A : O... | 11 | 0 |
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
... | 87 |
'''simple docstring'''
from collections.abc import Sequence
def _A ( _lowerCAmelCase = None ):
"""simple docstring"""
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
__lowercase =nums[0]
for i ... | 474 | 0 |
# 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... | 718 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('''3.8'''):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
__snake_case :int = ''''''
... | 60 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_ ( SCREAMING_SNAKE_CASE__ ) -> list:
if len(SCREAMING_SNAKE_CASE__ ) == 0:
return []
a_ , a_ : Dict = min(SCREAMING_SNAKE_CASE__ ), max(SCREAMING_SNAKE_CASE__ )
a_ : ... | 237 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE_ = ... | 237 | 1 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
_A : Optional[int] =300 # TEMPERATURE (unit = K)
def SCREAMING_SNAKE_CASE_ (UpperCamelCase , UpperCamelCase , UpperCamelCase , ) ... | 631 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vis... | 631 | 1 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowerCAmelCase : np.ndarray , lowerCAmelCase : np.ndarray , lowerCAmelCase : float = 1E-1_2 , lowerCAmelCase : int = 100 , ) -> tuple[float, np.ndarray]:
... | 373 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impor... | 373 | 1 |
from __future__ import annotations
from collections import Counter
from random import random
class _a :
"""simple docstring"""
def __init__( self ):
_lowercase ={}
def __lowerCAmelCase ( self , lowerCAmelCase_ ):
_lowercase ={}
def __lowerCAmelCase ( ... | 594 | import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table import ar... | 594 | 1 |
def __lowerCamelCase ( ):
'''simple docstring'''
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = 1
snake_cas... | 362 |
'''simple docstring'''
class _a :
"""simple docstring"""
def __init__( self , A__ ) -> List[Any]:
# we need a list not a string, so do something to change the type
_SCREAMING_SNAKE_CASE = arr.split(""",""" )
def Upp... | 591 | 0 |
'''simple docstring'''
def UpperCAmelCase_ (__a : List[Any] ):
"""simple docstring"""
_a : Any = [0] * len(__a )
_a : Optional[Any] = []
_a : Union[str, Any] = []
_a : Union[str, Any] = 0
for values in graph.... | 319 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerM... | 319 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobe... | 69 |
'''simple docstring'''
import enum
import shutil
import sys
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE = shutil.get_terminal_size()
__SCREAMING_SNAKE_CASE = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class lowerCAmelCase__ ( enum.Enum ):
"""... | 688 | 0 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import Ba... | 721 |
import pytest
import datasets
# Import fixture modules as plugins
_lowerCamelCase = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __UpperCAmelCase( lowercase_ , lowercase_ ):
# Mark tests as "unit" by default if not marked as "integration" ... | 613 | 0 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def A_ ( _lowerCAmelCase : Optional[Any] ):
... | 44 |
"""simple docstring"""
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
'''snap-research/efficientformer-l1-300''': (
'''https://huggingfa... | 465 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=_a ):
"""simple docstring"""
lowercase = ["sentencepiece"]
def __init__( self : List[Any] , *snake_case_ : Optional[Any] , **snake_case_ ... | 301 |
'''simple docstring'''
def __snake_case( _lowerCAmelCase , _lowerCAmelCase ) -> float:
if discount_rate < 0:
raise ValueError("""Discount rate cannot be negative""" )
if not cash_flows:
raise ValueError("""Cash flows list cannot be empty""" )
snake_case... | 301 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTester... | 76 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
__magic_name__ = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}
__magic_na... | 254 | 0 |
from typing import Any
def _lowerCamelCase( a ):
if not input_list:
return []
__a = [input_list.count(a ) for value in input_list]
__a = max(a ) # Gets the maximum count in the input list.
# Gets values of modes
return sorted(... | 708 | """simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class snake_case__ ( snake_case_ ):
def a__ ( self , lowerCamelCase ):
with open(lowerCamelCase , encoding="utf-8" ) as input_file:
... | 67 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenization... | 472 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __versi... | 472 | 1 |
'''simple docstring'''
def snake_case ( a_ : int ) -> "list[int]":
"""simple docstring"""
if upper_limit < 0:
raise ValueError("""Limit for the Catalan sequence must be ≥ 0""" )
UpperCamelCase_ : Optional[int] = [0] * (upper_l... | 543 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_com... | 543 | 1 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase( __snake_case ):
'''simple docstring'''
__magic_name__ = 'M-CLIP'
def __init__( self , snake_case_=1024 , snake_case_=768... | 27 |
__A : Dict = "Alexander Joslin"
import operator as op
from .stack import Stack
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
_A = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
... | 27 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A = {'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PLBartConfig'... | 703 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
'google/fnet-large': 'https://huggingface.co/google/fnet-... | 109 | 0 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch... | 101 | """simple docstring"""
from __future__ import annotations
import math
def lowerCamelCase_ ( __lowerCAmelCase , __lowerCAmelCase ) -> list:
'''simple docstring'''
if len(__lowerCAmelCase ) != 2 or len(a[0] ) != 2 or len(__lowerCAmelCase ) != 2 or ... | 530 | 0 |
'''simple docstring'''
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import tensorflow as tf... | 276 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"YituTech/conv-bert-base": "https... | 276 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class lowercase_ :
"""simple docstring"""
SCREAMING_SNAKE_CASE : int
SCREAMING_... | 41 |
"""simple docstring"""
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
_lowercase = {
'''User-Agent''': '''Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'''
''' (KHTML, like Gecko) Chrome/70.0.3538.... | 118 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : Tuple= logging.get_logger(__name__)
_a : Optional[int]= {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4... | 703 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_a : Optional[Any]= {
"configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG... | 192 | 0 |
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