code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
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 W... | 705 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 613 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetConfig''', '... | 706 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from ... | 613 | 0 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConf... | 707 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 613 | 0 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urll... | 708 |
_lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def __... | 613 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InformerConfig',
],
}
try:... | 709 |
import math
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = len(lowercase_ )
_lowerCamelCase : Optional[int] = int(math.floor(math.sqrt(lowercase_ ) ) )
_lowerCamelCase : Tuple = 0
w... | 613 | 0 |
def __UpperCAmelCase( lowercase_ = 10**12 ):
_lowerCamelCase : Union[str, Any] = 1
_lowerCamelCase : List[Any] = 0
_lowerCamelCase : Optional[int] = 1
_lowerCamelCase : Union[str, Any] = 1
while numerator <= 2 * min_tota... | 710 |
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... | 613 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
_lowerCamelCase = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
... | 711 |
def __UpperCAmelCase( lowercase_ ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : List[str]... | 613 | 0 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..... | 712 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 613 | 0 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {'vocab_file': 'vocab.json'}
_lowerCamelCase = {
'vocab_fi... | 713 |
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float(moles / volume ) * nfactor )
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float((moles * 0.0_8_2_1 * temperature) / (volume) ) ... | 613 | 0 |
'''simple docstring'''
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
_lowerCamelCase = logging.getLogger(__name__)
class __A ( __lowerCamelCase... | 714 |
import qiskit
def __UpperCAmelCase( lowercase_ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Optional[int] = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acting on the... | 613 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class __A ( _UpperCa... | 715 |
import unittest
from knapsack import knapsack as k
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
_lowerCamelCase : Dict = 0
_lowerCamelCase ... | 613 | 0 |
from bisect import bisect
from itertools import accumulate
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ , lowercase_ ):
_lowerCamelCase : Optional[int] = sorted(zip(a__ , a__ ) , key=lambda lowercase_ : x[0] / x[1] , reverse=a__ )
... | 716 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , ... | 613 | 0 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_config... | 717 |
import warnings
from .generation import TFGenerationMixin
class __A ( lowerCamelCase__ ):
"""simple docstring"""
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed... | 613 | 0 |
import copy
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 ..auto import CONFIG_MAPPING
_lowerCamelCase = logging.get_logger(__nam... | 718 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 613 | 0 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoModelWithLMHead,
... | 719 |
# 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 app... | 613 | 0 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ , ):
for nxt, d in graph... | 720 |
def __UpperCAmelCase( lowercase_ = 10_00 ):
_lowerCamelCase : Optional[int] = 2**power
_lowerCamelCase : Optional[int] = 0
while n:
_lowerCamelCase, _lowerCamelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__... | 613 | 0 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __A ( _snake_case ):
"""simple docstring"""
def... | 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 numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
_lowerCamelCase = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Mu... | 700 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requi... | 613 | 0 |
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
_lowerCamelCase ... | 701 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 613 | 0 |
import re
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : List[Any] = re.compile(r'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(lowerCamelCase_ , lowerCamelCase_ ):
return match.string == phone
return False
if ... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_roberta_prelayernorm': [
'ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIV... | 613 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig'... | 613 | 0 |
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,
... | 704 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CO... | 613 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase ... | 705 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 613 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {'configuration_reformer': ['REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ReformerConf... | 706 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from ... | 613 | 0 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __UpperCAmelCase( lowercase_ ):
def wrapper(*lowercase_ , **lowercase_ ):
_lowerCamelCas... | 707 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 613 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'
... | 708 |
_lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def __... | 613 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __A ( __A ):
"""simple docstring"""
UpperCAmelCase__ = """ClapFeatureExtractor"""
UpperCAmelCase__ = ("""RobertaTokenizer""", """RobertaT... | 709 |
import math
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = len(lowercase_ )
_lowerCamelCase : Optional[int] = int(math.floor(math.sqrt(lowercase_ ) ) )
_lowerCamelCase : Tuple = 0
w... | 613 | 0 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 710 |
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... | 613 | 0 |
'''simple docstring'''
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for... | 711 |
def __UpperCAmelCase( lowercase_ ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : List[str]... | 613 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils import logging
logging.... | 712 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 613 | 0 |
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,
... | 713 |
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float(moles / volume ) * nfactor )
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float((moles * 0.0_8_2_1 * temperature) / (volume) ) ... | 613 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_availa... | 714 |
import qiskit
def __UpperCAmelCase( lowercase_ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Optional[int] = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acting on the... | 613 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __A ( lo... | 715 |
import unittest
from knapsack import knapsack as k
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
_lowerCamelCase : Dict = 0
_lowerCamelCase ... | 613 | 0 |
from __future__ import annotations
import time
import numpy as np
_lowerCamelCase = [8, 5, 9, 7]
_lowerCamelCase = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_lowerCamelCase = [
[3, 2, 1, 4],
[0, 2, 5, 2],
... | 716 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , ... | 613 | 0 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _inte... | 717 |
import warnings
from .generation import TFGenerationMixin
class __A ( lowerCamelCase__ ):
"""simple docstring"""
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed... | 613 | 0 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transforme... | 718 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 613 | 0 |
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class __A ( UpperCamelCase_ ):
"""simple docstring"""
UpperCAmelCase__ = """MCTCTFeatureExtractor"""
UpperCAmelCase__ = """AutoTokenizer"""
... | 719 |
# 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 app... | 613 | 0 |
'''simple docstring'''
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 Opti... | 720 |
def __UpperCAmelCase( lowercase_ = 10_00 ):
_lowerCamelCase : Optional[int] = 2**power
_lowerCamelCase : Optional[int] = 0
while n:
_lowerCamelCase, _lowerCamelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__... | 613 | 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 __A ( lowerCamelCase__ ,unittest.TestCase ):
"""simple docstring"""
UpperC... | 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 unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 700 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requi... | 613 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class __A ( lowerCamelCase__ )... | 701 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 613 | 0 |
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load_metric
from .utils i... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_roberta_prelayernorm': [
'ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIV... | 613 | 0 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
_lowerCamelCase : Tuple = 0
if start < end:
_lowerCamelCase : int = randint(lowercase_ , lower... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig'... | 613 | 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
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
... | 704 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CO... | 613 | 0 |
_lowerCamelCase = {
0: '0',
1: '1',
2: '2',
3: '3',
4: '4',
5: '5',
6: '6',
7: '7',
8: '8',
9: '9',
10: 'a',
11: 'b',
12: 'c',
13: 'd',
14: 'e',
15: 'f',
}
def __UpperCAmelCase( lowercase_ ):
'''simple docstring... | 705 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 613 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
... | 706 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from ... | 613 | 0 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 707 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 613 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'andreasmadsen/efficient_mlm_m0.40':... | 708 |
_lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def __... | 613 | 0 |
import argparse
import os
import re
_lowerCamelCase = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCamelCase = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCamelCase = re.compile(r'^\s*"([^"]+)":')... | 709 |
import math
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = len(lowercase_ )
_lowerCamelCase : Optional[int] = int(math.floor(math.sqrt(lowercase_ ) ) )
_lowerCamelCase : Tuple = 0
w... | 613 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if i... | 710 |
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... | 613 | 0 |
'''simple docstring'''
import warnings
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
_lowerCamelCase = logging.get_logger(__name__)
... | 711 |
def __UpperCAmelCase( lowercase_ ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : List[str]... | 613 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if i... | 712 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 613 | 0 |
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is_tf_available() an... | 713 |
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float(moles / volume ) * nfactor )
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float((moles * 0.0_8_2_1 * temperature) / (volume) ) ... | 613 | 0 |
'''simple docstring'''
def __UpperCAmelCase( lowercase_ ):
return str(lowercase_ ) == str(lowercase_ )[::-1]
def __UpperCAmelCase( lowercase_ ):
return int(lowercase_ ) + int(str(lowercase_ )[::-1] )
def __UpperCAmelCase( lowerc... | 714 |
import qiskit
def __UpperCAmelCase( lowercase_ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Optional[int] = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acting on the... | 613 | 0 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
... | 715 |
import unittest
from knapsack import knapsack as k
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
_lowerCamelCase : Dict = 0
_lowerCamelCase ... | 613 | 0 |
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassification,
MobileViTVa... | 716 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , ... | 613 | 0 |
def __UpperCAmelCase( ):
_lowerCamelCase : int = []
_lowerCamelCase : Union[str, Any] = 1
while len(lowercase_ ) < 1e6:
constant.append(str(lowercase_ ) )
i += 1
_lowerCamelCase : str = ''''''.join(lower... | 717 |
import warnings
from .generation import TFGenerationMixin
class __A ( lowerCamelCase__ ):
"""simple docstring"""
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed... | 613 | 0 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_torch,
... | 718 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 613 | 0 |
from __future__ import annotations
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ , lowercase_ ): # noqa: E741
while r - l > 1:
_lowerCamelCase : str = (l + r) // 2
if v[m] >= key:
_lowerCamelCase : ... | 719 |
# 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 app... | 613 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __A ( unittest.TestCase ,lowerCamelCase__ ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstrin... | 720 |
def __UpperCAmelCase( lowercase_ = 10_00 ):
_lowerCamelCase : Optional[int] = 2**power
_lowerCamelCase : Optional[int] = 0
while n:
_lowerCamelCase, _lowerCamelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__... | 613 | 0 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import Co... | 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 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, prepare_image_inputs
if is_tor... | 700 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requi... | 613 | 0 |
import random
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : int = num - 1
_lowerCamelCase : Tuple = 0
while s % 2 == 0:
_lowerCamelCase : Tuple = s // 2
t += 1
for _ in range(5 ... | 701 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 613 | 0 |
import math
import qiskit
def __UpperCAmelCase( lowercase_ = 1 , lowercase_ = 1 , lowercase_ = 1 ):
if (
isinstance(lowercase_ , lowercase_ )
or isinstance(lowercase_ , lowercase_ )
or isinstance(lowercase_ , lowercase_ )
... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_roberta_prelayernorm': [
'ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIV... | 613 | 0 |
import itertools
import math
def __UpperCAmelCase( lowercase_ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not prim... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig'... | 613 | 0 |
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCamelCase = '▁'
_lo... | 704 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CO... | 613 | 0 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
_lowerCamelCase = False
class __A ( unittest.TestCase ):
"""simple docstring""... | 705 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 613 | 0 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ ... | 706 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from ... | 613 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCamelCase = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowerCo... | 707 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 613 | 0 |
from typing import Dict, Optional
import numpy as np
import datasets
_lowerCamelCase = '\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two classes) or multi-cl... | 708 |
_lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def __... | 613 | 0 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_lza, require... | 709 |
import math
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = len(lowercase_ )
_lowerCamelCase : Optional[int] = int(math.floor(math.sqrt(lowercase_ ) ) )
_lowerCamelCase : Tuple = 0
w... | 613 | 0 |
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : list[list[str]] = [[] for _ in range(lowercase_ )]
_lowerCamelCase : Any = key - 1
if key <= 0:
raise ValueError('''Height of grid can\'t be 0 or negative''' )
... | 710 |
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... | 613 | 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 require_tokenizers, slow... | 711 |
def __UpperCAmelCase( lowercase_ ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : List[str]... | 613 | 0 |
# 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 app... | 712 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 613 | 0 |
from math import factorial, radians
def __UpperCAmelCase( lowercase_ , lowercase_ = 18 , lowercase_ = 10 ):
_lowerCamelCase : List[Any] = angle_in_degrees - ((angle_in_degrees // 3_60.0) * 3_60.0)
# Converting from degrees to radians
_lowerCamelCase : ... | 713 |
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float(moles / volume ) * nfactor )
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float((moles * 0.0_8_2_1 * temperature) / (volume) ) ... | 613 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
# S... | 714 |
import qiskit
def __UpperCAmelCase( lowercase_ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Optional[int] = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acting on the... | 613 | 0 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
# Construct model
... | 715 |
import unittest
from knapsack import knapsack as k
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
_lowerCamelCase : Dict = 0
_lowerCamelCase ... | 613 | 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 = logging.get_logger(__name__)
_lowerCamelCase = '▁'... | 716 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , ... | 613 | 0 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
)
from tr... | 717 |
import warnings
from .generation import TFGenerationMixin
class __A ( lowerCamelCase__ ):
"""simple docstring"""
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed... | 613 | 0 |
def __UpperCAmelCase( lowercase_ = 10_00 ):
_lowerCamelCase : Optional[int] = 2**power
_lowerCamelCase : Optional[int] = 0
while n:
_lowerCamelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__ == "__main__":
... | 718 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 613 | 0 |
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" ... | 719 |
# 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 app... | 613 | 0 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class __A :
"""simple docstring"""
def __init__( self , a__=None , a__=None):
"""simple docstring"""
_lowerCamelCase : Any = ... | 720 |
def __UpperCAmelCase( lowercase_ = 10_00 ):
_lowerCamelCase : Optional[int] = 2**power
_lowerCamelCase : Optional[int] = 0
while n:
_lowerCamelCase, _lowerCamelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__... | 613 | 0 |
_lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def __... | 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 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 ac... | 700 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requi... | 613 | 0 |
def __UpperCAmelCase( lowercase_ , lowercase_ ):
return abs(lowercase_ ) if a == 0 else greatest_common_divisor(b % a , lowercase_ )
def __UpperCAmelCase( lowercase_ , lowercase_ ):
while y: # --> when y=0 then loop will terminate and re... | 701 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 613 | 0 |
import qiskit
def __UpperCAmelCase( lowercase_ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Optional[int] = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acting on the... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_roberta_prelayernorm': [
'ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIV... | 613 | 0 |
from __future__ import annotations
def __UpperCAmelCase( lowercase_ , lowercase_ ):
print(F"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(lowercase_ ):
print(F"""{i}\t\t{d}""" )
def __UpperCAmelCase( lowercase_ ,... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig'... | 613 | 0 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transforme... | 704 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CO... | 613 | 0 |
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ..... | 705 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 613 | 0 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 706 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from ... | 613 | 0 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
_lowerCamelCase = False
class __A (... | 707 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 613 | 0 |
def __UpperCAmelCase( lowercase_ ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : List[str]... | 708 |
_lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def __... | 613 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamel... | 709 |
import math
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = len(lowercase_ )
_lowerCamelCase : Optional[int] = int(math.floor(math.sqrt(lowercase_ ) ) )
_lowerCamelCase : Tuple = 0
w... | 613 | 0 |
from __future__ import annotations
class __A :
"""simple docstring"""
def __init__( self , a__=None):
"""simple docstring"""
_lowerCamelCase : Union[str, Any] = data
_lowerCamelCase : Union[str, ... | 710 |
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... | 613 | 0 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __A ( unittest.TestCase ):
"""simple docstr... | 711 |
def __UpperCAmelCase( lowercase_ ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : List[str]... | 613 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils imp... | 712 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 613 | 0 |
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : Union[str, Any] = [1]
_lowerCamelCase : List[str] = 0, 0, 0
_lowerCamelCase : Optional[int] = ugly_nums[ia] * 2
_lowerCamelCase : int = ugly_nums[ia] * 3
_lowerCamelCa... | 713 |
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float(moles / volume ) * nfactor )
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float((moles * 0.0_8_2_1 * temperature) / (volume) ) ... | 613 | 0 |
'''simple docstring'''
import heapq
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Priority Queue
... | 714 |
import qiskit
def __UpperCAmelCase( lowercase_ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Optional[int] = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acting on the... | 613 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if i... | 715 |
import unittest
from knapsack import knapsack as k
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
_lowerCamelCase : Dict = 0
_lowerCamelCase ... | 613 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType
... | 716 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , ... | 613 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.