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"""
import argparse
import os
from accelerate.utils import ComputeEnvironment
from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file # noqa: F401
from .config_utils import _ask_field, _ask_options, _conve... | 703 |
"""simple docstring"""
import os
def snake_case ( ) -> Optional[Any]:
with open(os.path.dirname(UpperCamelCase__ ) + """/grid.txt""" ) as f:
lowerCamelCase : int = [] # noqa: E741
for _ in range(20 ):
l.append([int(UpperCame... | 42 | 0 |
"""simple docstring"""
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_tor... | 704 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import ... | 42 | 0 |
"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def snake_case ( UpperCamelCase__ : bytes , UpperCamelCase__ : int ) -> np.array:
lowerCamelCase : List[str] =... | 705 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_atten... | 42 | 0 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowerCamelCase :str = get_tests_dir... | 706 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowerCamelCase :str = get_tests_dir... | 42 | 0 |
import math
import tensorflow as tf
from packaging import version
def snake_case ( UpperCamelCase__ : List[Any] ) -> Tuple:
lowerCamelCase : Optional[Any] = tf.convert_to_tensor(UpperCamelCase__ )
lowerCamelCase : List[str] = 0.5 * (1.0 + ... | 707 |
"""simple docstring"""
__lowerCamelCase :List[Any] = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
__lowerCamelCase :Union[str, Any] = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def snake_case ( UpperCamelCase__ : dict[int, list[int]] , UpperCamelCase__ ... | 42 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device... | 708 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase :str = logging.get_logger(__name__)
__lowerCamelCase :Any = {
'huggingface/time-series-transformer-tourism-monthly': (
... | 42 | 0 |
"""simple docstring"""
def snake_case ( UpperCamelCase__ : int = 4000000 ) -> int:
lowerCamelCase : List[Any] = [0, 1]
lowerCamelCase : Optional[Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib... | 709 |
"""simple docstring"""
from __future__ import annotations
__lowerCamelCase :int = 10
def snake_case ( UpperCamelCase__ : list[int] ) -> list[int]:
lowerCamelCase : int = 1
lowerCamelCase : Union[str, Any] = max(UpperCamelCase__ ... | 42 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case ( UpperCamelCase__ : ... | 710 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case ( UpperCamelCase__ : Optional[Any] ... | 42 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Backbo... | 711 |
"""simple docstring"""
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerate.te... | 42 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def snake_case ( UpperCamelCase__ : float , UpperCamelCase__ : int ) -> float:
lowerCamelCase : Dict = u
for i in range(1 , UpperCamelCase__ ):
lower... | 712 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__lowerCamelCase :Optional[Any] = {
'configuration_encodec': [
'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
'EncodecConfig',
... | 42 | 0 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class A__ ( datasets.BuilderConfig):
"""simple docstring"""
snake_case__ : Opti... | 713 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Backbo... | 42 | 0 |
"""simple docstring"""
import json
import sys
def snake_case ( UpperCamelCase__ : Any , UpperCamelCase__ : Tuple ) -> Tuple:
with open(UpperCamelCase__ , encoding="""utf-8""" ) as f:
lowerCamelCase : str = json.load(UpperCa... | 714 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase :Optional[int] = logging.get_logger(__name__)
__lowerCamelCase :List[str] = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/real... | 42 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class A__ ... | 715 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase :Tuple = logging.get_logger(__name__)
__lowerCamelCase :Any = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
# S... | 42 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase :str = {
'configuration_resnet': ['RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ResN... | 716 |
"""simple docstring"""
from __future__ import annotations
import math
def snake_case ( UpperCamelCase__ : float , UpperCamelCase__ : int ) -> float:
lowerCamelCase : Dict = u
for i in range(1 , UpperCamelCase__ ):
lower... | 42 | 0 |
"""simple docstring"""
import math
class A__ :
"""simple docstring"""
def a__ ( self: str , __a: list[list[float]] , __a: list[int] )-> int:
lowerCamelCase : Dict = 0.0
lowerCamelCase : Tuple = 0.0
for... | 717 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__lowerCamelCase :str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 42 | 0 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class A__ ( __lowercase):
"""simple docstring"""
snake_case__ : Tuple =(KDPMaDiscreteScheduler,)
sn... | 718 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from... | 42 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...featu... | 719 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class A__ ( __lowercase):
"""simple docstring"""
snake_case__ : Tuple =(KDPMaDiscreteScheduler,)
sn... | 42 | 0 |
"""simple docstring"""
def snake_case ( UpperCamelCase__ : int ) -> bool:
if num < 0:
return False
lowerCamelCase : int = num
lowerCamelCase : int = 0
while num > 0:
lowerCamelCase : Optional[Any] ... | 720 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLImga... | 42 | 0 |
"""simple docstring"""
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
__lowerCamelCase :str = collections.namedtuple('_... | 721 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identifie... | 42 | 0 |
'''simple docstring'''
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def __lowerCamelCase ( _UpperCamelC... | 43 | '''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : str , _UpperCamelCase : list[str] ):
'''simple docstring'''
UpperCAmelCase_ = ''''''
for word_or_phrase in separated:
if not isinstance(_UpperCamelCase , _UpperCamelCase ... | 43 | 1 |
'''simple docstring'''
lowercase__ : Dict = [0, 2, 4, 6, 8]
lowercase__ : str = [1, 3, 5, 7, 9]
def __lowerCamelCase ( _UpperCamelCase : int , _UpperCamelCase : int , _UpperCamelCase : list[int] , _UpperCamelCase : int ):
''... | 43 | '''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import... | 43 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowercase__ : Optional[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDep... | 43 | '''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : List[str] = {
"huggingface/time-series-transformer-tourism-monthly": (... | 43 | 1 |
'''simple docstring'''
from collections.abc import Callable
def __lowerCamelCase ( _UpperCamelCase : Callable[[float], float] , _UpperCamelCase : float , _UpperCamelCase : float ):
'''simple docstring'''
UpperCAmelCase_ = a
UpperCAmelCase_ ... | 43 | '''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : List[Any] = "T5Config"
class ... | 43 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : list , _UpperCamelCase : int = 0 ):
'''simple docstring'''
UpperCAmelCase_ = length or len(_UpperCamelCase )
UpperCAmelCase_ = False
for i in range(length - 1 ):
... | 43 | '''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
lowercase__ : str = datasets.logging.get_logger(__name__)
lowercase__ : Dict = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and ... | 43 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_... | 43 | '''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavingTestMix... | 43 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : int = 100 ):
'''simple docstring'''
UpperCAmelCase_ = n * (n + 1) * (2 * n + 1) / 6
UpperCAmelCase_ = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__... | 43 | '''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
f... | 43 | 1 |
'''simple docstring'''
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : List[str] = {
"vocab_file": "voca... | 43 | '''simple docstring'''
from collections.abc import Callable
def __lowerCamelCase ( _UpperCamelCase : Callable[[float], float] , _UpperCamelCase : float , _UpperCamelCase : float ):
'''simple docstring'''
UpperCAmelCase_ = a
UpperCAmelCase_ ... | 43 | 1 |
'''simple docstring'''
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 lowerCamelCase ( lowerCamelCase ):
'''simple docstri... | 43 | '''simple docstring'''
import re
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple docstring'''
return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple d... | 43 | 1 |
'''simple docstring'''
lowercase__ : List[Any] = {
"a": "AAAAA",
"b": "AAAAB",
"c": "AAABA",
"d": "AAABB",
"e": "AABAA",
"f": "AABAB",
"g": "AABBA",
"h": "AABBB",
"i": "ABAAA",
"j": "BBBAA",
"k": "ABAAB",
"l": "ABABA",
"m": "ABABB",
"n": "ABBAA",
... | 43 | '''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_... | 43 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
A... | 43 | '''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowercase__ : Tuple = pytest.mark.integration
@pytest.mark.parametrize('... | 43 | 1 |
'''simple docstring'''
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
lowercase__ : List[str] = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=Non... | 43 | '''simple docstring'''
import collections
import os
import re
from pathlib import Path
lowercase__ : List[Any] = "src/transformers"
# Matches is_xxx_available()
lowercase__ : Optional[Any] = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerc... | 43 | 1 |
'''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
lowercase__ : Dict = logging.getLogger(__name__)
if is_torch_tp... | 43 | '''simple docstring'''
from __future__ import annotations
def __lowerCamelCase ( _UpperCamelCase : tuple[int, int] , _UpperCamelCase : int ):
'''simple docstring'''
UpperCAmelCase_ , UpperCAmelCase_ = position
UpperCAmelCase_ = [
... | 43 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowercase__ : int = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def __lowerCamelC... | 43 | '''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = 42
lowerCAmelCase__ = 42
def __lowerCamelCase ( _UpperCamelCase : str ):
... | 43 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, Reg... | 43 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase__ : Union[str, Any] = {
"configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_A... | 43 | 1 |
'''simple docstring'''
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRIN... | 43 | '''simple docstring'''
lowercase__ : Union[str, Any] = "\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"
lowercase__ : str = [{"type": "code", "con... | 43 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : Optional[int] ):
'''simple docstring'''
UpperCAmelCase_ = len(_UpperCamelCase )
for i in range(length - 1 ):
UpperCAmelCase_ = i
for k in range(i + 1 , ... | 43 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Optional[Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
]... | 43 | 1 |
'''simple docstring'''
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's easier to... | 43 | '''simple docstring'''
from heapq import heappop, heappush
import numpy as np
def __lowerCamelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : tuple[int, int] , _UpperCamelCase : tuple[int, int] , _UpperCamelCase : bool , ):
'''simple docstring'... | 43 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = 42
lowerCAmelCase__ = 42
def __lowerCamelCase ( _UpperCamelCase : str ):
... | 43 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase ( lowerCamelCase , unittest.... | 43 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[int] = logging.get_logger(__name__)
lowercase__ : Any = {
"tiiuae/falcon-40b": "https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json",
... | 43 | '''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __lowerCamelCase ( _UpperCamelCase : Union[str, Any] ):
'''simple docstring'''
for param in module.parameters():
UpperCAmelCase_ = False
def __lowerCame... | 43 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def __lowerCamelCase ( _UpperCamelCase : Sequence[int] | None = None ):
'''simple docstring'''
if nums is None or not nums:
raise ValueError('''Input sequence should not be empty''' )
UpperCAmelCase_ ... | 43 | '''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require... | 43 | 1 |
'''simple docstring'''
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def _... | 43 | '''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cach... | 43 | 1 |
'''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __lowerCamelCase ( _UpperCamelCase : Union[str, Any] ):
'''simple docstring'''
for param in module.parameters():
UpperCAmelCase_ = False
def __lowerCame... | 43 | '''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : str , _UpperCamelCase : list[str] ):
'''simple docstring'''
UpperCAmelCase_ = ''''''
for word_or_phrase in separated:
if not isinstance(_UpperCamelCase , _UpperCamelCase ... | 43 | 1 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_availabl... | 43 | '''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import... | 43 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from... | 43 | '''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : List[str] = {
"huggingface/time-series-transformer-tourism-monthly": (... | 43 | 1 |
'''simple docstring'''
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import st... | 43 | '''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : List[Any] = "T5Config"
class ... | 43 | 1 |
'''simple docstring'''
import os
def __lowerCamelCase ( ):
'''simple docstring'''
with open(os.path.dirname(_UpperCamelCase ) + '''/grid.txt''' ) as f:
UpperCAmelCase_ = [] # noqa: E741
for _ in range(20 ):
l.append([int(_... | 43 | '''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
lowercase__ : str = datasets.logging.get_logger(__name__)
lowercase__ : Dict = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and ... | 43 | 1 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowercase__ : List[str] = {
"facebook/maskformer-swi... | 43 | '''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavingTestMix... | 43 | 1 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple docstring'''
UpperCAmelCase... | 43 | '''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
f... | 43 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase :
'''simple docstring'''
def __init__( self : Optional[Any] , UpperCAmelCase__ : int ) ->None:
UpperCAmelCase_ = value
... | 43 | '''simple docstring'''
from collections.abc import Callable
def __lowerCamelCase ( _UpperCamelCase : Callable[[float], float] , _UpperCamelCase : float , _UpperCamelCase : float ):
'''simple docstring'''
UpperCAmelCase_ = a
UpperCAmelCase_ ... | 43 | 1 |
'''simple docstring'''
import math
def __lowerCamelCase ( _UpperCamelCase : float , _UpperCamelCase : float ):
'''simple docstring'''
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of neg... | 43 | '''simple docstring'''
import re
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple docstring'''
return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple d... | 43 | 1 |
'''simple docstring'''
from manim import *
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
def lowerCAmelCase__ ( self : Any ) ->Dict:
UpperCAmelCase_ = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase_ = Rect... | 43 | '''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_... | 43 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : Tuple = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.js... | 43 | '''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowercase__ : Tuple = pytest.mark.integration
@pytest.mark.parametrize('... | 43 | 1 |
'''simple docstring'''
# using dfs for finding eulerian path traversal
def __lowerCamelCase ( _UpperCamelCase : Tuple , _UpperCamelCase : Dict , _UpperCamelCase : Optional[Any] , _UpperCamelCase : List[str]=None ):
'''simple docstring'''
UpperCAmelCa... | 43 | '''simple docstring'''
import collections
import os
import re
from pathlib import Path
lowercase__ : List[Any] = "src/transformers"
# Matches is_xxx_available()
lowercase__ : Optional[Any] = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerc... | 43 | 1 |
'''simple docstring'''
from math import ceil
def __lowerCamelCase ( _UpperCamelCase : int = 1001 ):
'''simple docstring'''
UpperCAmelCase_ = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
UpperCAmelCase_ = 2 * i + 1
... | 43 | '''simple docstring'''
from __future__ import annotations
def __lowerCamelCase ( _UpperCamelCase : tuple[int, int] , _UpperCamelCase : int ):
'''simple docstring'''
UpperCAmelCase_ , UpperCAmelCase_ = position
UpperCAmelCase_ = [
... | 43 | 1 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowercase__ : Optional[int] = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-traine... | 43 | '''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = 42
lowerCAmelCase__ = 42
def __lowerCamelCase ( _UpperCamelCase : str ):
... | 43 | 1 |
'''simple docstring'''
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def __lowerCamelCase ( _UpperCamelCase : List[str] ):
'''simple docstring'''
UpperCAmelCase_ = args.pruning_met... | 43 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase__ : Union[str, Any] = {
"configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_A... | 43 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
... | 43 | '''simple docstring'''
lowercase__ : Union[str, Any] = "\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"
lowercase__ : str = [{"type": "code", "con... | 43 | 1 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MA... | 43 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Optional[Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
]... | 43 | 1 |
'''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowercase__ : Tuple = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation}... | 43 | '''simple docstring'''
from heapq import heappop, heappush
import numpy as np
def __lowerCamelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : tuple[int, int] , _UpperCamelCase : tuple[int, int] , _UpperCamelCase : bool , ):
'''simple docstring'... | 43 | 1 |
'''simple docstring'''
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
lowercase__ : List[Any] = object()
# For specifying empty leaf dict `{}`
lowercase__ : str =... | 43 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase ( lowerCamelCase , unittest.... | 43 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitC... | 43 | '''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __lowerCamelCase ( _UpperCamelCase : Union[str, Any] ):
'''simple docstring'''
for param in module.parameters():
UpperCAmelCase_ = False
def __lowerCame... | 43 | 1 |
'''simple docstring'''
import os
import jsonlines
import numpy as np
from tqdm import tqdm
lowercase__ : Dict = 2048
lowercase__ : Dict = 4096
lowercase__ : List[Any] = 42
lowercase__ : List[str] = os.environ.pop("PROCESS_TRAIN", "false")
lowercase_... | 43 | '''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require... | 43 | 1 |
'''simple docstring'''
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_devic... | 43 | '''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cach... | 43 | 1 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model... | 43 | '''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : str , _UpperCamelCase : list[str] ):
'''simple docstring'''
UpperCAmelCase_ = ''''''
for word_or_phrase in separated:
if not isinstance(_UpperCamelCase , _UpperCamelCase ... | 43 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
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 flax.jax_u... | 43 | '''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import... | 43 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Tuple = logging.get_logger(__name__)
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = '''timm_backbone'''
... | 43 | '''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : List[str] = {
"huggingface/time-series-transformer-tourism-monthly": (... | 43 | 1 |
'''simple docstring'''
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
'''split_dict''' , [
SplitDict(),
SplitDict({'''train''': SplitInfo(name='''train''' , num_bytes=1337 , num_exampl... | 43 | '''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : List[Any] = "T5Config"
class ... | 43 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : str = logging.get_logger(__name__)
lowercase__ : Optional[Any] = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class lowerCamel... | 43 | '''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
lowercase__ : str = datasets.logging.get_logger(__name__)
lowercase__ : Dict = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and ... | 43 | 1 |
'''simple docstring'''
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
lowercase__ : str = Lock()
def __lowerCamelCase ( _UpperCamelCase : Dict , _UpperCamelCase : int , _UpperCamelCase ... | 43 | '''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavingTestMix... | 43 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_... | 43 | '''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
f... | 43 | 1 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
i... | 43 | '''simple docstring'''
from collections.abc import Callable
def __lowerCamelCase ( _UpperCamelCase : Callable[[float], float] , _UpperCamelCase : float , _UpperCamelCase : float ):
'''simple docstring'''
UpperCAmelCase_ = a
UpperCAmelCase_ ... | 43 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM... | 43 | '''simple docstring'''
import re
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple docstring'''
return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple d... | 43 | 1 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNot... | 43 | '''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_... | 43 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : Any = {
"configuration_convbert": ["CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP... | 43 | '''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowercase__ : Tuple = pytest.mark.integration
@pytest.mark.parametrize('... | 43 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
lowercase__ : Tuple = logging.get_logger(__name__)
class lowerCamelCase ( lowerCamelCase ):
'''simple docstr... | 43 | '''simple docstring'''
import collections
import os
import re
from pathlib import Path
lowercase__ : List[Any] = "src/transformers"
# Matches is_xxx_available()
lowercase__ : Optional[Any] = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerc... | 43 | 1 |
'''simple docstring'''
import numpy as np
def __lowerCamelCase ( _UpperCamelCase : np.array ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 43 | '''simple docstring'''
from __future__ import annotations
def __lowerCamelCase ( _UpperCamelCase : tuple[int, int] , _UpperCamelCase : int ):
'''simple docstring'''
UpperCAmelCase_ , UpperCAmelCase_ = position
UpperCAmelCase_ = [
... | 43 | 1 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class lowerCamelCase ( lowerCamelCase , unittest.TestCase ):
'''simple docstring'''
lowe... | 43 | '''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = 42
lowerCAmelCase__ = 42
def __lowerCamelCase ( _UpperCamelCase : str ):
... | 43 | 1 |
'''simple docstring'''
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... | 43 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase__ : Union[str, Any] = {
"configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_A... | 43 | 1 |
'''simple docstring'''
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
... | 43 | '''simple docstring'''
lowercase__ : Union[str, Any] = "\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"
lowercase__ : str = [{"type": "code", "con... | 43 | 1 |
'''simple docstring'''
import math
def __lowerCamelCase ( _UpperCamelCase : int ):
'''simple docstring'''
return math.sqrt(_UpperCamelCase ) * math.sqrt(_UpperCamelCase ) == num
def __lowerCamelCase ( _UpperCamelCase : int ):
'''simple docstring'... | 43 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Optional[Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
]... | 43 | 1 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
lowercase__ : str = "\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 43 | '''simple docstring'''
from heapq import heappop, heappush
import numpy as np
def __lowerCamelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : tuple[int, int] , _UpperCamelCase : tuple[int, int] , _UpperCamelCase : bool , ):
'''simple docstring'... | 43 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase__ : Union[str, Any] ... | 43 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase ( lowerCamelCase , unittest.... | 43 | 1 |
'''simple docstring'''
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
impo... | 43 | '''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __lowerCamelCase ( _UpperCamelCase : Union[str, Any] ):
'''simple docstring'''
for param in module.parameters():
UpperCAmelCase_ = False
def __lowerCame... | 43 | 1 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowerCamelCase ( _UpperCam... | 43 | '''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require... | 43 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Optional[Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
]... | 43 | '''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cach... | 43 | 1 |
'''simple docstring'''
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def __lowerCamelCase ( _UpperCamelCase : str , _UpperCamelCase : Any ):
'''simple docstring'''
Upp... | 43 | '''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : str , _UpperCamelCase : list[str] ):
'''simple docstring'''
UpperCAmelCase_ = ''''''
for word_or_phrase in separated:
if not isinstance(_UpperCamelCase , _UpperCamelCase ... | 43 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enab... | 43 | '''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import... | 43 | 1 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='''session''' )
def __lowerCamelCase ( ... | 43 | '''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : List[str] = {
"huggingface/time-series-transformer-tourism-monthly": (... | 43 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : int = 6008_5147_5143 ):
'''simple docstring'''
try:
UpperCAmelCase_ = int(_UpperCamelCase )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castab... | 43 | '''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : List[Any] = "T5Config"
class ... | 43 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : list ):
'''simple docstring'''
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
if len(_UpperCamelCase ... | 43 | '''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
lowercase__ : str = datasets.logging.get_logger(__name__)
lowercase__ : Dict = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and ... | 43 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : int , _UpperCamelCase : int ):
'''simple docstring'''
return 1 if input_a == input_a else 0
def __lowerCamelCase ( ):
'''simple docstring'''
assert xnor_gate(0 , 0 ) =... | 43 | '''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavingTestMix... | 43 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import lo... | 43 | '''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
f... | 43 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ : int = {
"configuration_graphormer": ["GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "GraphormerConfig"],
}
try:
... | 43 | '''simple docstring'''
from collections.abc import Callable
def __lowerCamelCase ( _UpperCamelCase : Callable[[float], float] , _UpperCamelCase : float , _UpperCamelCase : float ):
'''simple docstring'''
UpperCAmelCase_ = a
UpperCAmelCase_ ... | 43 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : int = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/c... | 43 | '''simple docstring'''
import re
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple docstring'''
return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple d... | 43 | 1 |
'''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : Dict... | 43 | '''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_... | 43 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : int ):
'''simple docstring'''
UpperCAmelCase_ = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 43 | '''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowercase__ : Tuple = pytest.mark.integration
@pytest.mark.parametrize('... | 43 | 1 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = (CMStochasticIterativeScheduler,)
lowerCAmelCase__ ... | 43 | '''simple docstring'''
import collections
import os
import re
from pathlib import Path
lowercase__ : List[Any] = "src/transformers"
# Matches is_xxx_available()
lowercase__ : Optional[Any] = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerc... | 43 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : int ):
'''simple docstring'''
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
UpperCAmelCase_ = F"""Input value of [number={number}] must be an integer"""
raise TypeE... | 43 | '''simple docstring'''
from __future__ import annotations
def __lowerCamelCase ( _UpperCamelCase : tuple[int, int] , _UpperCamelCase : int ):
'''simple docstring'''
UpperCAmelCase_ , UpperCAmelCase_ = position
UpperCAmelCase_ = [
... | 43 | 1 |
'''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowercase__ : Tuple = pytest.mark.integration
@pytest.mark.parametrize('... | 43 | '''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = 42
lowerCAmelCase__ = 42
def __lowerCamelCase ( _UpperCamelCase : str ):
... | 43 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDisc... | 43 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase__ : Union[str, Any] = {
"configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_A... | 43 | 1 |
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