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 |
|---|---|---|---|---|
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_convbert''': ['''CONVBERT_PRETRAINED_CON... | 707 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_availab... | 28 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
A_ = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer... | 708 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list[int] , snake_case__ : str ):
"""simple docstring"""
_snake_case : str = int(snake_case__ )
# Initialize Result
_snake_case : str = []
# Traverse through ... | 28 | 0 |
"""simple docstring"""
from timeit import timeit
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if number < 0:
raise ValueError("""the value of input must not be negative""" )
_snake_case : int = 0
while number:
number ... | 709 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision... | 28 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def UpperCAmelCase__ (snake_case__ : List[Any] ):
"""... | 710 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase( __a ):
'''simple docstring'''
lowercase__ = (IPNDMScheduler,)
lowercase__ ... | 28 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ = {
'''conf... | 711 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Nega... | 28 | 0 |
"""simple docstring"""
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_si... | 712 |
"""simple docstring"""
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transfo... | 28 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {'''configuration_opt''': ['''OPT_PRETRA... | 713 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if not isinstance(snake_case__ , snake_case__ ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
_snake_case : Dict = 0
... | 28 | 0 |
"""simple docstring"""
from collections import deque
def UpperCAmelCase__ (snake_case__ : Optional[int] ):
"""simple docstring"""
_snake_case : Dict = len(snake_case__ )
_snake_case : List[Any] = deque()
_snake_case : List[str] ... | 714 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_to... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
A_ = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
A_ ... | 715 |
"""simple docstring"""
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_si... | 28 | 0 |
"""simple docstring"""
from collections.abc import Callable
def UpperCAmelCase__ (snake_case__ : Callable[[float], float] , snake_case__ : float , snake_case__ : float ):
"""simple docstring"""
_snake_case : float = a
_snake_... | 716 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils impor... | 28 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : str , snake_case__ : str ):
"""simple docstring"""
assert x is not None
assert y is not None
_snake_case : List[str] = len(snake_case__ )
_snake_case : Any = ... | 717 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
A_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
A_ = [ord(letter) for letter in string.as... | 28 | 0 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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... | 718 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowercase( __a ):
'''simple docstring'''
lowercase__ = ["image_processor", "feature_extractor"]
lowercase__ = "TvltImageProcessor"
lowercase__ ... | 28 | 0 |
"""simple docstring"""
import sys
from collections import defaultdict
class lowercase:
'''simple docstring'''
def __init__( self: Optional[Any] ):
'''simple docstring'''
_snake_case : Any = []
def Upper... | 719 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tok... | 28 | 0 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
A_ = ''''''
A_ = ''''''
A_ = ''''''
A_ = 1 # (0 is vertical, 1 is horizontal)
def UpperCAmelCase__ ():
"""simpl... | 720 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowercase( __a ):
'''simple docstring'''
@staticmethod
@abstractmethod
def UpperCamelCase_ ( a_: ArgumentParser ):
'''simp... | 28 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class lowercase( ... | 721 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''junnyu/roformer_... | 28 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
_snake_case : Optional[Any] = 2
_snake_case : List[str] = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
... | 700 |
"""simple docstring"""
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def UpperCAmelCase__ (snake_case__ : Optional[Any] , snake_case__ : Union[str, Any]=1 ):
"""simple docstring"""
if... | 28 | 0 |
"""simple docstring"""
import numpy as np
def UpperCAmelCase__ (snake_case__ : np.array ):
"""simple docstring"""
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 701 |
"""simple docstring"""
from typing import Any
def UpperCAmelCase__ (snake_case__ : list ):
"""simple docstring"""
if not input_list:
return []
_snake_case : List[Any] = [input_list.count(snake_case__ ) for value in input_list]
_snake_case ... | 28 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : int , snake_case__ : int ):
"""simple docstring"""
if not isinstance(snake_case__ , snake_case__ ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance... | 702 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''BridgeTower/bridgetower-base''': '''https://huggingface.co/Brid... | 28 | 0 |
"""simple docstring"""
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.... | 703 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
... | 28 | 0 |
import itertools
import math
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
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 ... | 704 |
"""simple docstring"""
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,
Mobi... | 28 | 0 |
"""simple docstring"""
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
... | 705 |
"""simple docstring"""
import os
import sys
import unittest
A_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files... | 28 | 0 |
"""simple docstring"""
from math import ceil
def UpperCAmelCase__ (snake_case__ : int = 10_01 ):
"""simple docstring"""
_snake_case : Any = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
_snake_case : int = 2 * i + 1
... | 706 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ = {
'''conf... | 28 | 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 Ara... | 707 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_availab... | 28 | 0 |
"""simple docstring"""
A_ = [
'''Audio''',
'''Array2D''',
'''Array3D''',
'''Array4D''',
'''Array5D''',
'''ClassLabel''',
'''Features''',
'''Sequence''',
'''Value''',
'''Image''',
'''Translation''',
'''TranslationVariableLanguages''',... | 708 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list[int] , snake_case__ : str ):
"""simple docstring"""
_snake_case : str = int(snake_case__ )
# Initialize Result
_snake_case : str = []
# Traverse through ... | 28 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import Model... | 709 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision... | 28 | 0 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_... | 710 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase( __a ):
'''simple docstring'''
lowercase__ = (IPNDMScheduler,)
lowercase__ ... | 28 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_roformer''': [''... | 711 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Nega... | 28 | 0 |
"""simple docstring"""
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 ImageProcessingSav... | 712 |
"""simple docstring"""
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transfo... | 28 | 0 |
"""simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorTyp... | 713 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if not isinstance(snake_case__ , snake_case__ ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
_snake_case : Dict = 0
... | 28 | 0 |
"""simple docstring"""
import copy
import random
from transformers import CLIPTokenizer
class lowercase( __a ):
'''simple docstring'''
def __init__( self: Optional[int], *a_: Optional[Any], **a_: Dict ):
'''simple docstring'''
... | 714 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_to... | 28 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
Aut... | 715 |
"""simple docstring"""
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_si... | 28 | 0 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
A_ = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: imp... | 716 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils impor... | 28 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : int , snake_case__ : int ):
"""simple docstring"""
while a != 0:
_snake_case : Tuple = b % a, a
return b
def UpperCAmelCase__ (snake_case__ : int ... | 717 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
A_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
A_ = [ord(letter) for letter in string.as... | 28 | 0 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def UpperCAmelCase__ ():
"""simple docstring"""
_snake_case : Union[str, Any] = ArgumentParser(
description=(... | 718 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowercase( __a ):
'''simple docstring'''
lowercase__ = ["image_processor", "feature_extractor"]
lowercase__ = "TvltImageProcessor"
lowercase__ ... | 28 | 0 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, S... | 719 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tok... | 28 | 0 |
"""simple docstring"""
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
A_ = logging.get_... | 720 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowercase( __a ):
'''simple docstring'''
@staticmethod
@abstractmethod
def UpperCamelCase_ ( a_: ArgumentParser ):
'''simp... | 28 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (snake_case__ : list[int | str] ):
"""simple docstring"""
create_state_space_tree(snake_case__ , [] , 0 , [0 for i in range(len(snake_case__ ) )] )
def Upper... | 721 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''junnyu/roformer_... | 28 | 0 |
"""simple docstring"""
import warnings
from functools import wraps
from typing import Callable
def UpperCAmelCase__ (snake_case__ : Callable ):
"""simple docstring"""
@wraps(snake_case__ )
def _inner_fn(*snake_case__ : Any , **snake_case__ : Tuple )... | 700 |
"""simple docstring"""
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def UpperCAmelCase__ (snake_case__ : Optional[Any] , snake_case__ : Union[str, Any]=1 ):
"""simple docstring"""
if... | 28 | 0 |
"""simple docstring"""
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelFo... | 701 |
"""simple docstring"""
from typing import Any
def UpperCAmelCase__ (snake_case__ : list ):
"""simple docstring"""
if not input_list:
return []
_snake_case : List[Any] = [input_list.count(snake_case__ ) for value in input_list]
_snake_case ... | 28 | 0 |
"""simple docstring"""
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
A_ = logging.getLogger(__name__)
if is... | 702 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''BridgeTower/bridgetower-base''': '''https://huggingface.co/Brid... | 28 | 0 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowercase:
'''simple docstring'''
def __init__( self: List[str], a_: Optional[Any] ):
'''simple docstring'''
_snake_case : Union[str, Any] =... | 703 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
... | 28 | 0 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available(... | 704 |
"""simple docstring"""
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,
Mobi... | 28 | 0 |
"""simple docstring"""
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 ... | 705 |
"""simple docstring"""
import os
import sys
import unittest
A_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files... | 28 | 0 |
"""simple docstring"""
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def UpperCAmelCase__ (snake_case__ : Optional[Any] , snake_case__ : Union[str, Any]=1 ):
"""simple docstring"""
if... | 706 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ = {
'''conf... | 28 | 0 |
"""simple docstring"""
from typing import Any
class lowercase:
'''simple docstring'''
def __init__( self: Union[str, Any], a_: Any ):
'''simple docstring'''
_snake_case : int = data
_snake_case : List[str]... | 707 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_availab... | 28 | 0 |
"""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/def... | 708 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list[int] , snake_case__ : str ):
"""simple docstring"""
_snake_case : str = int(snake_case__ )
# Initialize Result
_snake_case : str = []
# Traverse through ... | 28 | 0 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from tran... | 709 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision... | 28 | 0 |
"""simple docstring"""
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip instal... | 710 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase( __a ):
'''simple docstring'''
lowercase__ = (IPNDMScheduler,)
lowercase__ ... | 28 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils imp... | 711 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Nega... | 28 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterM... | 712 |
"""simple docstring"""
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transfo... | 28 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {'''configuration_xlnet''': [''... | 713 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if not isinstance(snake_case__ , snake_case__ ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
_snake_case : Dict = 0
... | 28 | 0 |
"""simple docstring"""
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def UpperCAmelCase__ (*snake_case__ : List[Any] , snake_case__ : Optional[Union[Dict, Any]] = None , snake_case__ : st... | 714 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_to... | 28 | 0 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def UpperCAmelCase__ ():
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname ... | 715 |
"""simple docstring"""
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_si... | 28 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class lowercase:
'''simple docstring'''
def __init__( self: Union[str, Any], a_: int = 6 ):
'''simple docstring'''
_snake_case : Node | No... | 716 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils impor... | 28 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_commo... | 717 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
A_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
A_ = [ord(letter) for letter in string.as... | 28 | 0 |
def UpperCAmelCase__ (snake_case__ : str , snake_case__ : str ):
"""simple docstring"""
def get_matched_characters(snake_case__ : str , snake_case__ : str ) -> str:
_snake_case : str = []
_snake_case : Any ... | 718 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowercase( __a ):
'''simple docstring'''
lowercase__ = ["image_processor", "feature_extractor"]
lowercase__ = "TvltImageProcessor"
lowercase__ ... | 28 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_c... | 719 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tok... | 28 | 0 |
"""simple docstring"""
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
A_ = HfArgumentParser(InitializationArguments)
A_ = parser.parse_args()
# Load codeparro... | 720 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowercase( __a ):
'''simple docstring'''
@staticmethod
@abstractmethod
def UpperCamelCase_ ( a_: ArgumentParser ):
'''simp... | 28 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowercase:
'''simple docstring'''
lowercase__ = field(
default="codeparrot/codeparrot" , metadata={"help": "Model name or pa... | 721 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''junnyu/roformer_... | 28 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"xlm-mlm-en-2048": "https://huggingface.co/xlm-mlm-en-2048/resolve/main/conf... | 29 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __A ( lowerCAmelCase ):
'''simple docstring'''
lowerCAmelCase_ = """ClapFeatureExtractor"""
lowerCAmelCase_ = ("""RobertaTokenizer""", """RobertaToken... | 29 | 1 |
from math import ceil
def lowerCAmelCase__(__snake_case = 1001 ) -> int:
'''simple docstring'''
lowerCamelCase__ = 1
for i in range(1 ,int(ceil(n / 2.0 ) ) ):
lowerCamelCase__ = 2 * i + 1
lowerCamelCase__ = 2 * i
l... | 29 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pip... | 29 | 1 |
import numpy
# List of input, output pairs
_a = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
_a = (((515, 22, 13), 555), ((61, 35, 49), 150))
_a = [2, 4, 1, 5]
_a = len(train_data)
_a = 0.009
def lowerCAm... | 29 |
import string
from math import logaa
def lowerCAmelCase__(__snake_case ,__snake_case ) -> int:
'''simple docstring'''
lowerCamelCase__ = document.translate(
str.maketrans('''''' ,'''''' ,string.punctuation ) ).replace('''\n''' ,'''''' )
lower... | 29 | 1 |
def lowerCAmelCase__(__snake_case = 50000000 ) -> int:
'''simple docstring'''
lowerCamelCase__ = set()
lowerCamelCase__ = int((limit - 24) ** (1 / 2) )
lowerCamelCase__ = set(range(3 ,prime_square_limit + 1 ,2 ) )
primes.ad... | 29 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_a = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
"convert_funnel_origin... | 29 | 1 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
_a = 4
_a = 3
class __A ( lowerCAmelCase ):
'''simple docstring'''
... | 29 |
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_a = namedtuple(
"_TestCommandArgs",
[
"dataset",
"name",
... | 29 | 1 |
from manim import *
class __A ( lowerCAmelCase ):
'''simple docstring'''
def __lowerCamelCase ( self ):
'''simple docstring'''
lowerCamelCase__ = Rectangle(height=0.5 , width=0.5 )
lowerCamelCase__ = R... | 29 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_atten... | 29 | 1 |
from PIL import Image
def lowerCAmelCase__(__snake_case ,__snake_case ) -> Image:
'''simple docstring'''
def brightness(__snake_case ) -> float:
return 128 + level + (c - 128)
if not -2_5_5.0 <= level <= 2_5_5.0:
raise ValueError('''level must be between -255.0 (blac... | 29 |
from math import sqrt
def lowerCAmelCase__(__snake_case ) -> bool:
'''simple docstring'''
assert isinstance(__snake_case ,__snake_case ) and (
number >= 0
), "'number' must been an int and positive"
lowerCamelCase__ = True
# 0 and 1 are none primes.
... | 29 | 1 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_a = logging.get_logger(__name__)
class __A ( lowerCAmelCase ):
'''simple docstring'''
def __init__( self , *__lowerCAmelCase , **__lowerCAmelCase ... | 29 |
from __future__ import annotations
def lowerCAmelCase__(__snake_case ,__snake_case = None ,__snake_case = None ) -> None:
'''simple docstring'''
if start is None:
lowerCamelCase__ = 0
if end is None:
lowerCamelCase__ = len(__snake_case ) - 1... | 29 | 1 |
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 = logging.get_logger(__name__)
_a = {
"salesforce/bl... | 29 |
from __future__ import annotations
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ) -> float:
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError('''days_between_payments must be > 0''' )
if daily_interest_rate < 0:
raise ValueError('... | 29 | 1 |
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformers import Au... | 29 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def lowerCAmelCase__(__snake_case ) -> Union[str, Any]:
'''simple docstring'''
def wrapper(*__snake_case ,**__snake_case ):
lo... | 29 | 1 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common impor... | 29 |
def lowerCAmelCase__(__snake_case ) -> int:
'''simple docstring'''
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 ,len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
lowerCa... | 29 | 1 |
from __future__ import annotations
import os
from collections.abc import Mapping
_a = tuple[int, int]
class __A :
'''simple docstring'''
def __init__( self , __lowerCAmelCase , __lowerCAmelCase ):
'''simple docstring'''
lowerCamelCase__ ... | 29 |
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... | 29 | 1 |
_a = "\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
_a = [{"type": "code", "content": INSTALL_CONTENT}]
_a = {
"{processor_class}": "FakeProcessorC... | 29 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_a = datasets.logging.get_logger(__name__)
_a = "\\n@InProceedings{moosavi2019minimum,\n author = { Nafise Sadat Moosavi, Leo B... | 29 | 1 |
def lowerCAmelCase__(__snake_case = 1000000 ) -> int:
'''simple docstring'''
lowerCamelCase__ = set(range(3 ,__snake_case ,2 ) )
primes.add(2 )
for p in range(3 ,__snake_case ,2 ):
if p not in primes:
continue
primes.difference_update(set... | 29 |
# 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 tests
from os.path import j... | 29 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"andreasmadsen/efficient_mlm_m0.40": (
"https://huggingface.co/andre... | 29 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
_a = logging.get_logger(__name__)
class __A :
'''simple docstring'''
lowerCAmelCase_ = None
@experimental
def lowerCAmelCase__(__sna... | 29 | 1 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_a = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 29 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class __A ... | 29 | 1 |
def lowerCAmelCase__(__snake_case ) -> str:
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 29 |
_a = "\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
_a = [{"type": "code", "content": INSTALL_CONTENT}]
_a = {
"{processor_class}": "FakeProcessorC... | 29 | 1 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_a = logging.getLogger(__name__)
class __A :
'''simple docstring'''
def __init__( self ):
... | 29 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_a = {
"configuration_gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig", "GPTNeoOnnxConfig"],
}
try:
if not is_torch_available():
raise ... | 29 | 1 |
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
_a ... | 29 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_a = logging.get_logger(__name__)
class __A ( lowerCAmelCase ):
'''simple docstring'''
def __init__( self , *__lowerCAmelCase , **__lowerCAmelCase ... | 29 | 1 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,) -> float | int:
'''simple docstring'''
for nxt, d in graph[v]... | 29 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ) -> Any:
'''simple docstring'''
lowerCamelCase__ = {
'''en''': '''Machine learning is great, isn\'t it?''',
... | 29 | 1 |
import torch
from transformers import AutoModel
class __A ( torch.nn.Module ):
'''simple docstring'''
def __init__( self , __lowerCAmelCase="sayef/fsner-bert-base-uncased" ):
'''simple docstring'''
super(__lowerCAmelCase , self ).__... | 29 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
_a = logging.get_logger(__name__)
class __A ( lowerCAmelCase ):
'''simple docstring'''
def __init__( self , *__lowerCAmelCase , **__lowerCAmelCa... | 29 | 1 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowerCAmelCase__(__snake_case ) -> List[Any]:
'''simple docstring'''
if "model" in orig_key:
lowerCamelCase__ = orig_key.replace('''model.''' ,'''''' )
if "norm1" in ori... | 29 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,) -> float | int:
'''simple docstring'''
for nxt, d in graph[v]... | 29 | 1 |
from math import log
from scipy.constants import Boltzmann, physical_constants
_a = 300 # TEMPERATURE (unit = K)
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,) -> float:
'''simple docstring'''
if donor_conc <= 0:
raise ValueError('''Donor concentration sh... | 29 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __A ( lowerCAmelCase ):
'''simple docstring'''
lowerCAmelCase_ = """ClapFeatureExtractor"""
lowerCAmelCase_ = ("""RobertaTokenizer""", """RobertaToken... | 29 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_a = logging.get_logger(__name__)
# TODO: upload to AWS
_a = {
"yjernite/retribert-base-uncased": (
"https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"
),
}
class... | 29 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pip... | 29 | 1 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ) -> str:
'''simple docstring'''
lo... | 29 |
import string
from math import logaa
def lowerCAmelCase__(__snake_case ,__snake_case ) -> int:
'''simple docstring'''
lowerCamelCase__ = document.translate(
str.maketrans('''''' ,'''''' ,string.punctuation ) ).replace('''\n''' ,'''''' )
lower... | 29 | 1 |
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property
from ...test_... | 29 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_a = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
"convert_funnel_origin... | 29 | 1 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def lowerCAmelCase__(__snake_case ) -> Union[str, Any]:
'''simple docstring'''
def wrapper(*__snake_case ,**__snake_case ):
lo... | 29 |
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_a = namedtuple(
"_TestCommandArgs",
[
"dataset",
"name",
... | 29 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"edbeeching/decision-transformer-gym-hopper-medium": (
"https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"
),
... | 29 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_atten... | 29 | 1 |
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
_a = logging.get_logger(__name__)
class __A ( lowerCAmelCase ):
'''simple docstring'''
def __init__( self , *__lowerCAmelCase , **__l... | 29 |
from math import sqrt
def lowerCAmelCase__(__snake_case ) -> bool:
'''simple docstring'''
assert isinstance(__snake_case ,__snake_case ) and (
number >= 0
), "'number' must been an int and positive"
lowerCamelCase__ = True
# 0 and 1 are none primes.
... | 29 | 1 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a n... | 29 |
from __future__ import annotations
def lowerCAmelCase__(__snake_case ,__snake_case = None ,__snake_case = None ) -> None:
'''simple docstring'''
if start is None:
lowerCamelCase__ = 0
if end is None:
lowerCamelCase__ = len(__snake_case ) - 1... | 29 | 1 |
from __future__ import annotations
import math
def lowerCAmelCase__(__snake_case ,__snake_case ) -> list:
'''simple docstring'''
if len(__snake_case ) != 2 or len(a[0] ) != 2 or len(__snake_case ) != 2 or len(b[0] ) != 2:
raise Exception('''Matrices ar... | 29 |
from __future__ import annotations
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ) -> float:
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError('''days_between_payments must be > 0''' )
if daily_interest_rate < 0:
raise ValueError('... | 29 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pip... | 29 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def lowerCAmelCase__(__snake_case ) -> Union[str, Any]:
'''simple docstring'''
def wrapper(*__snake_case ,**__snake_case ):
lo... | 29 | 1 |
def lowerCAmelCase__(__snake_case ,__snake_case ) -> list:
'''simple docstring'''
lowerCamelCase__ = word.split()
def justify(__snake_case ,__snake_case ,__snake_case ) -> str:
lowerCamelCase__ = max_width - width
lowerCamelCase__ = ... | 29 |
def lowerCAmelCase__(__snake_case ) -> int:
'''simple docstring'''
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 ,len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
lowerCa... | 29 | 1 |
from __future__ import annotations
def lowerCAmelCase__(__snake_case ,__snake_case = None ,__snake_case = None ) -> None:
'''simple docstring'''
if start is None:
lowerCamelCase__ = 0
if end is None:
lowerCamelCase__ = len(__snake_case ) - 1... | 29 |
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... | 29 | 1 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
_a = logging.get_logger(__name__)
class __A :
'''simple docstring'''
lowerCAmelCase_ = None
@experimental
def lowerCAmelCase__(__sna... | 29 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_a = datasets.logging.get_logger(__name__)
_a = "\\n@InProceedings{moosavi2019minimum,\n author = { Nafise Sadat Moosavi, Leo B... | 29 | 1 |
import string
from math import logaa
def lowerCAmelCase__(__snake_case ,__snake_case ) -> int:
'''simple docstring'''
lowerCamelCase__ = document.translate(
str.maketrans('''''' ,'''''' ,string.punctuation ) ).replace('''\n''' ,'''''' )
lower... | 29 |
# 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 tests
from os.path import j... | 29 | 1 |
from __future__ import annotations
import math
def lowerCAmelCase__(__snake_case ,__snake_case ) -> float:
'''simple docstring'''
lowerCamelCase__ = u
for i in range(1 ,__snake_case ):
lowerCamelCase__ = temp * (u - i)
return temp
def lo... | 29 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
_a = logging.get_logger(__name__)
class __A :
'''simple docstring'''
lowerCAmelCase_ = None
@experimental
def lowerCAmelCase__(__sna... | 29 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_a = {
"configuration_falcon": ["FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP", "FalconConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAva... | 29 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class __A ... | 29 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 29 |
_a = "\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
_a = [{"type": "code", "content": INSTALL_CONTENT}]
_a = {
"{processor_class}": "FakeProcessorC... | 29 | 1 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs("hub/hopper-medium-v2/unet/hor32", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/unet/hor128", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/value_function", exist_ok=True)
def lowerCAmelCase__(__snake_case ) ... | 29 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_a = {
"configuration_gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig", "GPTNeoOnnxConfig"],
}
try:
if not is_torch_available():
raise ... | 29 | 1 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case = None ,__snake_case = None ,__snake_case = None ,) -> Tup... | 29 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_a = logging.get_logger(__name__)
class __A ( lowerCAmelCase ):
'''simple docstring'''
def __init__( self , *__lowerCAmelCase , **__lowerCAmelCase ... | 29 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.