code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowercase :
def __init__( self):
lowercase = ''''''
lowercase = ''''''
lowercase = []
lowercase = 0
... | 101 |
"""simple docstring"""
from string import ascii_uppercase
_A = {str(ord(c) - 5_5): c for c in ascii_uppercase}
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
if isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise TypeEr... | 242 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__)
SCREAMING_S... | 102 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase = 0 ) -> list:
lowerCAmelCase__ : Optional[Any] = length or len(__UpperCAmelCase )
lowerCAmelCase__ : int = False
for i in range(length - 1 ):
... | 242 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
A__ : Tuple = logging.get_logger(__name__)
A__ : List[str] ... | 103 |
"""simple docstring"""
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowercase_ ( __UpperCAmelCase ) ->... | 242 | 0 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def _A ( A__ , A__ , A__ , A__ , A__ ):
"""simple docstring"""
__lowercase = cva.getAffineTransform(A__ , A__ )
return c... | 104 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
fro... | 242 | 0 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
fr... | 105 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_A = logging.get_logger(__name__)
_A = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/r... | 242 | 0 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenize... | 106 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase = 1000 ) -> int:
lowerCAmelCase__ : Optional[Any] = 2**power
lowerCAmelCase__ : Optional[int] = str(__UpperCAmelCase )
lowerCAmelCase__ : Optional[int] = list(__Upper... | 242 | 0 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...... | 107 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 242 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Traj... | 108 |
"""simple docstring"""
import math
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
lowerCAmelCase__ : Any = len(__UpperCAmelCase )
lowerCAmelCase__ : int = int(math.floor(math.sqrt(__UpperCAmelCase ) ) )
... | 242 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
A: str = logging.getLogger(__name__)
def _snake_case ( ):
UpperCAmelCase : List[str] = argparse.ArgumentParser(
description="""Prepa... | 109 |
"""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
_A = logging.get_logger(__name__)
class _lowerCamelCase :
def __init__( sel... | 242 | 0 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase__ ( a_ , unittest.TestCase ):
A__ : List[Any] =CTRLTokenizer
A__ : ... | 176 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> int:
def count_of_possible_combinations(__UpperCAmelCase ) -> int:
if target < 0:
return 0
if target == 0:
r... | 242 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import choice
def _A ( snake_case ) -> Optional[Any]:
return choice(__UpperCAmelCase )
def _A ( snake_case , snake_case ) -> int:
_lowercase : List[str] = random_pivot(__UpperC... | 250 |
"""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/LICENSE-2... | 242 | 0 |
def __magic_name__ ( ):
'''simple docstring'''
for n in range(1 , 1_000_000 ):
yield n * (n + 1) // 2
def __magic_name__ ( __a : List[Any] ):
'''simple docstring'''
UpperCamelCase__ = 1
UpperCamelCase__ = 2
... | 244 |
"""simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( __UpperCAmelCase ) -> bool:
return np.array_equal(__UpperCAmelCase , matrix.conjugate().T )
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> Any:
... | 242 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
__A = logging.get_logger(__name__)
__A = {
'''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''',
# See all DPT ... | 135 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class _lowerCamelCase ( a_ ):
def _lowerCAmelCase ( self : Any ) -> str:
"""simple docstring"""
return [
... | 242 | 0 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(a_ ) , """Tatoeba directory d... | 209 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 242 | 0 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowerCamelCase : Dict = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', defaul... | 2 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transf... | 242 | 0 |
import os
from datetime import datetime as dt
from github import Github
lowerCAmelCase__ : Tuple = [
'''good first issue''',
'''feature request''',
'''wip''',
]
def UpperCamelCase__ ( ) -> List[str]:
snake_case__ : List[str] = Github(os.environ[... | 143 |
"""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 = logging.get_logger(__name__)
_A = {
"""face... | 242 | 0 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _SCREAMING_SNAKE_CASE ( a_ ):
'''simple docstring'''
lowercase_ = (DDPMParallelScheduler,)
def SCREAMING_SNAKE_CASE_ (self : Dict , **UpperCAmelCase_ ... | 10 |
"""simple docstring"""
from __future__ import annotations
import bisect
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
if hi < 0:
lowerCAmelCase__ : Union[str, Any] = len(__Uppe... | 242 | 0 |
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 Blondel, M. and Pr... | 119 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax... | 242 | 0 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_s... | 259 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( __UpperCAmelCase ) -> int:
if not nums:
return 0
lowerCAmelCase__ : List[Any] = nums[0]
lowerCAmelCase__ : List[str] = 0
for num in nums[1:]:
... | 242 | 0 |
def a ( A__ : Optional[Any] ) -> str:
"""simple docstring"""
return "".join(chr(ord(__UpperCAmelCase ) - 32 ) if 'a' <= char <= 'z' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 205 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowercase_ ( ) -> Optional[int]:
lowerCAmelCase__ : Dict = {
"""repo_name""": ["""test_repo1""... | 242 | 0 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowercase__ ( a_ , unittest.TestCase ):
A__ : ... | 176 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoT... | 242 | 0 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.schedulers.scheduling_utils import SchedulerMixin
from diffusers.utils import ... | 250 |
"""simple docstring"""
from itertools import product
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> list[int]:
lowerCAmelCase__ : Union[str, Any] = sides_number
lowerCAmelCase__ : Optional[int] = max_face_number * dice_number
... | 242 | 0 |
import copy
import random
from transformers import CLIPTokenizer
class __A( a_ ):
"""simple docstring"""
def __init__(self , *SCREAMING_SNAKE_CASE_ , **SCREAMING_SNAKE_CASE_ ):
super().__init__(*SCREAMING_SNAKE_CASE_ , **SCREAMING_SNAKE_CASE_ )
Upper... | 244 |
"""simple docstring"""
from string import ascii_uppercase
_A = {str(ord(c) - 5_5): c for c in ascii_uppercase}
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
if isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise TypeEr... | 242 | 0 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__A = argparse.ArgumentParser()
parser.add_argument('''--dump_path''', default=None, type=... | 135 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase = 0 ) -> list:
lowerCAmelCase__ : Optional[Any] = length or len(__UpperCAmelCase )
lowerCAmelCase__ : int = False
for i in range(length - 1 ):
... | 242 | 0 |
def lowerCAmelCase__(__snake_case ) -> bool:
'''simple docstring'''
if number < 0:
raise ValueError('''number must not be negative''' )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 209 |
"""simple docstring"""
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowercase_ ( __UpperCAmelCase ) ->... | 242 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE (A = 1_000 ) -> int:
"""simple docstring"""
lowercase__ = 2**power
lowercase__ = str(__UpperCAmelCase )
lowercase__ = list(__UpperCAmelCase )
lowercase__ ... | 2 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
fro... | 242 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelera... | 143 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_A = logging.get_logger(__name__)
_A = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/r... | 242 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}
class _SCREAMING_SNAKE_CASE ( a_ ):
... | 10 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase = 1000 ) -> int:
lowerCAmelCase__ : Optional[Any] = 2**power
lowerCAmelCase__ : Optional[int] = str(__UpperCAmelCase )
lowerCAmelCase__ : Optional[int] = list(__Upper... | 242 | 0 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRetr... | 119 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 242 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class UpperCAmelCase_ ( unittest.TestCase ):
"""sim... | 259 |
"""simple docstring"""
import math
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
lowerCAmelCase__ : Any = len(__UpperCAmelCase )
lowerCAmelCase__ : int = int(math.floor(math.sqrt(__UpperCAmelCase ) ) )
... | 242 | 0 |
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
lowercase_ =... | 205 |
"""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
_A = logging.get_logger(__name__)
class _lowerCamelCase :
def __init__( sel... | 242 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from transfo... | 176 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> int:
def count_of_possible_combinations(__UpperCAmelCase ) -> int:
if target < 0:
return 0
if target == 0:
r... | 242 | 0 |
'''simple docstring'''
def _A ( snake_case ) -> str:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 250 |
"""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/LICENSE-2... | 242 | 0 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCamelCase_ = '''src/transformers'''
# Matches is_xxx_available()
lowerCamelCase_ = re.compile(r'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
lowerCamelCase_ = re.c... | 244 |
"""simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( __UpperCAmelCase ) -> bool:
return np.array_equal(__UpperCAmelCase , matrix.conjugate().T )
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> Any:
... | 242 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_... | 135 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class _lowerCamelCase ( a_ ):
def _lowerCAmelCase ( self : Any ) -> str:
"""simple docstring"""
return [
... | 242 | 0 |
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_clip": [
"CLIP_PRETRAINED_CONFIG_... | 209 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 242 | 0 |
'''simple docstring'''
import os
def _SCREAMING_SNAKE_CASE () -> Tuple:
"""simple docstring"""
lowercase__ = os.path.dirname(os.path.realpath(__UpperCAmelCase ) )
lowercase__ = os.path.join(__UpperCAmelCase , '''triangle.txt''' )... | 2 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transf... | 242 | 0 |
lowerCAmelCase__ : Optional[int] = [0, 2, 4, 6, 8]
lowerCAmelCase__ : Tuple = [1, 3, 5, 7, 9]
def UpperCamelCase__ ( A__ , A__ , A__ , A__ ) -> int:
if remaining_length == 0:
if digits[0] == 0 or digits[-1] == 0:
return 0
for i in range(l... | 143 |
"""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 = logging.get_logger(__name__)
_A = {
"""face... | 242 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__A = logging.get_logger(__name__)
class _SCREAMING_SNA... | 10 |
"""simple docstring"""
from __future__ import annotations
import bisect
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
if hi < 0:
lowerCAmelCase__ : Union[str, Any] = len(__Uppe... | 242 | 0 |
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
__UpperCAmelCase = ge... | 119 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax... | 242 | 0 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 259 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( __UpperCAmelCase ) -> int:
if not nums:
return 0
lowerCAmelCase__ : List[Any] = nums[0]
lowerCAmelCase__ : List[str] = 0
for num in nums[1:]:
... | 242 | 0 |
def a ( A__ : Optional[Any] , A__ : int , A__ : Dict ) -> int:
"""simple docstring"""
def count_of_possible_combinations(A__ : List[str] ) -> int:
if target < 0:
return 0
if target == 0:
... | 205 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowercase_ ( ) -> Optional[int]:
lowerCAmelCase__ : Dict = {
"""repo_name""": ["""test_repo1""... | 242 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not is_torch_available():
... | 176 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoT... | 242 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class a__ :
def __init__( self , _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
if len(_UpperCamelCase ) != degree + 1:
raise ValueError(
... | 250 |
"""simple docstring"""
from itertools import product
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> list[int]:
lowerCAmelCase__ : Union[str, Any] = sides_number
lowerCAmelCase__ : Optional[int] = max_face_number * dice_number
... | 242 | 0 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
import s... | 244 |
"""simple docstring"""
from string import ascii_uppercase
_A = {str(ord(c) - 5_5): c for c in ascii_uppercase}
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
if isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise TypeEr... | 242 | 0 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class _snake_case ( datasets.BeamBasedBuilder ):
def lowerCamelCase... | 135 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase = 0 ) -> list:
lowerCAmelCase__ : Optional[Any] = length or len(__UpperCAmelCase )
lowerCAmelCase__ : int = False
for i in range(length - 1 ):
... | 242 | 0 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as Pr... | 209 |
"""simple docstring"""
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowercase_ ( __UpperCAmelCase ) ->... | 242 | 0 |
'''simple docstring'''
from typing import Any
def _SCREAMING_SNAKE_CASE (A ) -> list[Any]:
"""simple docstring"""
if not input_list:
return []
lowercase__ = [input_list.count(__UpperCAmelCase ) for value in input_list]
lowe... | 2 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
fro... | 242 | 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
lowerCAmelCase__ : List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ ... | 143 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_A = logging.get_logger(__name__)
_A = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/r... | 242 | 0 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_I... | 10 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase = 1000 ) -> int:
lowerCAmelCase__ : Optional[Any] = 2**power
lowerCAmelCase__ : Optional[int] = str(__UpperCAmelCase )
lowerCAmelCase__ : Optional[int] = list(__Upper... | 242 | 0 |
import tensorflow as tf
from ...tf_utils import shape_list
class lowerCAmelCase_ ( tf.keras.layers.Layer ):
def __init__( self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_=1, SCREAMING_SNAKE_CASE_=False, **S... | 119 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 242 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import torch
if is_vision_avail... | 259 |
"""simple docstring"""
import math
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
lowerCAmelCase__ : Any = len(__UpperCAmelCase )
lowerCAmelCase__ : int = int(math.floor(math.sqrt(__UpperCAmelCase ) ) )
... | 242 | 0 |
def a ( A__ : List[str] ) -> bool:
"""simple docstring"""
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
_lowercase =F'''Input value of [number={number}] must be an integer'''
raise TypeError(__UpperCAmelCa... | 205 |
"""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
_A = logging.get_logger(__name__)
class _lowerCamelCase :
def __init__( sel... | 242 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}
class lowercase__ ( ... | 176 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> int:
def count_of_possible_combinations(__UpperCAmelCase ) -> int:
if target < 0:
return 0
if target == 0:
r... | 242 | 0 |
'''simple docstring'''
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
_snake_case = logging.get_logger(__name__)
_snake_case = '▁'
_snake_case =... | 250 |
"""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/LICENSE-2... | 242 | 0 |
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
lowerCamelCase_ = logging.get_logger(__name__)
class __A( a_ ):
"""simple docstring"""
def __init__(self , *SCREAMING_SNAKE_CASE_ , **SCREAMING_SNAKE_... | 244 |
"""simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( __UpperCAmelCase ) -> bool:
return np.array_equal(__UpperCAmelCase , matrix.conjugate().T )
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> Any:
... | 242 | 0 |
"""simple docstring"""
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
__A = {
'''Acehnese Arabic''': '''ace_Arab''',
'''Acehnese Latin''': '''ace_Latn''',
'''Mesopotamian Arabic''': '''acm_Arab''',
'''Ta\'izzi-Adeni Arabic''': '''acq_Arab''',
... | 135 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class _lowerCamelCase ( a_ ):
def _lowerCAmelCase ( self : Any ) -> str:
"""simple docstring"""
return [
... | 242 | 0 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_com... | 209 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 242 | 0 |
'''simple docstring'''
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_si... | 2 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transf... | 242 | 0 |
def UpperCamelCase__ ( A__ ) -> Optional[int]:
if not head:
return True
# split the list to two parts
snake_case__ : List[str] = head.next, head
while fast and fast.next:
snake_case__ : Any = fast.next.next
snake_ca... | 143 |
"""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 = logging.get_logger(__name__)
_A = {
"""face... | 242 | 0 |
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
__A = logging.get_logger(__name__)
def lowerCAmelCase_ ( ... | 10 |
"""simple docstring"""
from __future__ import annotations
import bisect
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
if hi < 0:
lowerCAmelCase__ : Union[str, Any] = len(__Uppe... | 242 | 0 |
from math import factorial
def UpperCamelCase ( snake_case__ : Tuple = 20 ) -> int:
UpperCamelCase : str = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCamelCase : Optional[int] = n // 2
return int(factorial(__UpperC... | 119 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax... | 242 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding,... | 259 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( __UpperCAmelCase ) -> int:
if not nums:
return 0
lowerCAmelCase__ : List[Any] = nums[0]
lowerCAmelCase__ : List[str] = 0
for num in nums[1:]:
... | 242 | 0 |
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 .... | 205 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowercase_ ( ) -> Optional[int]:
lowerCAmelCase__ : Dict = {
"""repo_name""": ["""test_repo1""... | 242 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
# See all GLPN models at https://huggingface.c... | 176 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoT... | 242 | 0 |
'''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
_snake_case = logging.get_logger(__name__)
_snake_case = {
'facebook/de... | 250 |
"""simple docstring"""
from itertools import product
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> list[int]:
lowerCAmelCase__ : Union[str, Any] = sides_number
lowerCAmelCase__ : Optional[int] = max_face_number * dice_number
... | 242 | 0 |
from __future__ import annotations
import bisect
def __magic_name__ ( __a : Any , __a : Optional[int] , __a : Tuple = 0 , __a : Union[str, Any] = -1 ):
'''simple docstring'''
if hi < 0:
UpperCamelCase__ = len(__U... | 244 |
"""simple docstring"""
from string import ascii_uppercase
_A = {str(ord(c) - 5_5): c for c in ascii_uppercase}
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
if isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise TypeEr... | 242 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowerCamelCase: Tuple ) -> bool:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = str(__UpperCAmelCase )
return len(__UpperCAmelCase ) == 9 and... | 135 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase = 0 ) -> list:
lowerCAmelCase__ : Optional[Any] = length or len(__UpperCAmelCase )
lowerCAmelCase__ : int = False
for i in range(length - 1 ):
... | 242 | 0 |
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 lowerCAmelCase__(__snake_case ) -> Any:
... | 209 |
"""simple docstring"""
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowercase_ ( __UpperCAmelCase ) ->... | 242 | 0 |
'''simple docstring'''
from typing import Any
def _SCREAMING_SNAKE_CASE (A , A , A , A , A , ) -> list:
"""simple docstring"""
_validation(
__UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , )
# Crea... | 2 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
fro... | 242 | 0 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTextCo... | 143 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_A = logging.get_logger(__name__)
_A = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/r... | 242 | 0 |
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,
MusicgenProcesso... | 10 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase = 1000 ) -> int:
lowerCAmelCase__ : Optional[Any] = 2**power
lowerCAmelCase__ : Optional[int] = str(__UpperCAmelCase )
lowerCAmelCase__ : Optional[int] = list(__Upper... | 242 | 0 |
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 is_torch_available()... | 119 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 242 | 0 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : Union[str, Any] ):
if not nums:
return 0
UpperCamelCase :List[Any] = nums[0]
UpperCamelCase :List[str] = 0
for num in nums[1:]:
UpperCamelCase :List[Any] ... | 259 |
"""simple docstring"""
import math
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
lowerCAmelCase__ : Any = len(__UpperCAmelCase )
lowerCAmelCase__ : int = int(math.floor(math.sqrt(__UpperCAmelCase ) ) )
... | 242 | 0 |
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
lowercase_ = logging.get_logger(__name__)
lowercase_ = 'T5Config'
def a ( A__ ... | 205 |
"""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
_A = logging.get_logger(__name__)
class _lowerCamelCase :
def __init__( sel... | 242 | 0 |
def _lowercase ( UpperCamelCase_ , UpperCamelCase_ ) -> str:
'''simple docstring'''
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise ValueError('iterations must be defined as integers' )
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ) or not numbe... | 176 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> int:
def count_of_possible_combinations(__UpperCAmelCase ) -> int:
if target < 0:
return 0
if target == 0:
r... | 242 | 0 |
'''simple docstring'''
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
_snake_case = '\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang, Alex an... | 250 |
"""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/LICENSE-2... | 242 | 0 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from torch import nn
from ... | 244 |
"""simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( __UpperCAmelCase ) -> bool:
return np.array_equal(__UpperCAmelCase , matrix.conjugate().T )
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> Any:
... | 242 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowerCamelCase: Optional[int] , _lowerCamelCase: List[Any] ) -> list[tuple[int, int]]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = position
... | 135 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class _lowerCamelCase ( a_ ):
def _lowerCAmelCase ( self : Any ) -> str:
"""simple docstring"""
return [
... | 242 | 0 |
from typing import List
import numpy as np
def lowerCAmelCase__(__snake_case ) -> int:
'''simple docstring'''
lowerCamelCase__ = {key: len(__UpperCAmelCase ) for key, value in gen_kwargs.items() if isinstance(__UpperCAmelCase ,__UpperCAmelCase )}
if l... | 209 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 242 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : Tuple = logging.get_logger(__name__)
lowerCamelCase : int = {
'... | 2 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transf... | 242 | 0 |
lowerCAmelCase__ : Any = [
'''Audio''',
'''Array2D''',
'''Array3D''',
'''Array4D''',
'''Array5D''',
'''ClassLabel''',
'''Features''',
'''Sequence''',
'''Value''',
'''Image''',
'''Translation''',
'''TranslationVariableLanguages''',
]
from .audio impo... | 143 |
"""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 = logging.get_logger(__name__)
_A = {
"""face... | 242 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class _SCREAMING_SNAKE_CASE ( a_ ):
'''simple docstring'''
lowercas... | 10 |
"""simple docstring"""
from __future__ import annotations
import bisect
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
if hi < 0:
lowerCAmelCase__ : Union[str, Any] = len(__Uppe... | 242 | 0 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCAmelCase_ :
def __init__( self, SCREAMING_SNAKE_CASE_ ) -> Any:
UpperCamelCase : Tuple = str(id_ )
UpperCamelCase : Dict = None
UpperCamelCase : L... | 119 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax... | 242 | 0 |
from itertools import product
def _A ( SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Optional[Any] ):
UpperCamelCase :Union[str, Any] = sides_number
UpperCamelCase :Optional[int] = max_face_number * dice_number
UpperCamelCase :... | 259 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( __UpperCAmelCase ) -> int:
if not nums:
return 0
lowerCAmelCase__ : List[Any] = nums[0]
lowerCAmelCase__ : List[str] = 0
for num in nums[1:]:
... | 242 | 0 |
from __future__ import annotations
from typing import Generic, TypeVar
lowercase_ = TypeVar('T')
class __lowerCAmelCase ( Generic[T] ):
def __init__( self , lowerCAmelCase ) -> None:
'''simple docstring'''
_lowercase ... | 205 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowercase_ ( ) -> Optional[int]:
lowerCAmelCase__ : Dict = {
"""repo_name""": ["""test_repo1""... | 242 | 0 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
__snake_case = logging.get_logger(__name__)
class lowercase__ ( a_ ):
def __init__( self : int , *UpperCAmelCase_ : Any , **UpperCAmelCase_ ... | 176 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoT... | 242 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def _A ( ) -> Optional[int]:
_lowercase : Dict = {
"""repo_name""": ["""test_repo1""", """test_repo2""", """test_re... | 250 |
"""simple docstring"""
from itertools import product
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> list[int]:
lowerCAmelCase__ : Union[str, Any] = sides_number
lowerCAmelCase__ : Optional[int] = max_face_number * dice_number
... | 242 | 0 |
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
lowerCamelCase_ = yaml.safe_load(
'''\
name: \"\"
allow_empty: false
allow_empty_text: true
subsections:
- name: \"Dataset Card fo... | 244 |
"""simple docstring"""
from string import ascii_uppercase
_A = {str(ord(c) - 5_5): c for c in ascii_uppercase}
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
if isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise TypeEr... | 242 | 0 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 135 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase = 0 ) -> list:
lowerCAmelCase__ : Optional[Any] = length or len(__UpperCAmelCase )
lowerCAmelCase__ : int = False
for i in range(length - 1 ):
... | 242 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
_a = False
class __A ( unittest.TestCase ):
'''simple docstr... | 209 |
"""simple docstring"""
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowercase_ ( __UpperCAmelCase ) ->... | 242 | 0 |
'''simple docstring'''
from math import factorial
lowerCamelCase : List[Any] = {str(d): factorial(d) for d in range(10)}
def _SCREAMING_SNAKE_CASE (A ) -> int:
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(__UpperCAmelCase ... | 2 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
fro... | 242 | 0 |
import baseaa
def UpperCamelCase__ ( A__ ) -> bytes:
return baseaa.aaaencode(string.encode('utf-8' ) )
def UpperCamelCase__ ( A__ ) -> str:
return baseaa.aaadecode(__UpperCAmelCase ).decode('utf-8' )
if __name__ == "__main__":
import doctest
d... | 143 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_A = logging.get_logger(__name__)
_A = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/r... | 242 | 0 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _SCREAMING_SNAKE_CASE ( a_ ):
'''simple docstring'''
lowercase_ = "Speech2TextFeatureExtractor"
lowercase_ = "Speech2TextTokenizer"
def __init__(self : List[str] ,... | 10 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase = 1000 ) -> int:
lowerCAmelCase__ : Optional[Any] = 2**power
lowerCAmelCase__ : Optional[int] = str(__UpperCAmelCase )
lowerCAmelCase__ : Optional[int] = list(__Upper... | 242 | 0 |
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def UpperCamelCase ( snake_case__ : List[Any] ) -> Dict:
UpperCamelCase : Optional[int] = [
"""encoder.version""",
"""decoder.version""",
"""mode... | 119 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 242 | 0 |
def _A ( SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : Tuple ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__UpperCAmelCase , int(b / 2 ) ) * actual_power(__UpperCAmelCase , int(b / 2 ) )
else:
... | 259 |
"""simple docstring"""
import math
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
lowerCAmelCase__ : Any = len(__UpperCAmelCase )
lowerCAmelCase__ : int = int(math.floor(math.sqrt(__UpperCAmelCase ) ) )
... | 242 | 0 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowercase_ = False
class __lowerCAmelCase ( unittest.TestCase ):... | 205 |
"""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
_A = logging.get_logger(__name__)
class _lowerCamelCase :
def __init__( sel... | 242 | 0 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_available():
... | 176 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> int:
def count_of_possible_combinations(__UpperCAmelCase ) -> int:
if target < 0:
return 0
if target == 0:
r... | 242 | 0 |
'''simple docstring'''
from __future__ import annotations
def _A ( snake_case ) -> list[int]:
_lowercase : List[Any] = [True] * limit
_lowercase : Dict = False
_lowercase : Optional[Any] = False
_lowercase : Union[str, Any] =... | 250 |
"""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/LICENSE-2... | 242 | 0 |
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase_ = datasets.load_iris()
lowerCamelCase_ = np.array(data['''data'''])
lowerCamelCase_ = np.array(data['''target'''])
lowerCamelCase_ ... | 244 |
"""simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( __UpperCAmelCase ) -> bool:
return np.array_equal(__UpperCAmelCase , matrix.conjugate().T )
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> Any:
... | 242 | 0 |
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