code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 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()
... | 610 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase__ = {"""UserAgent""": UserAgent().random}
def __lowerCamelCase ( __UpperCamelCase ) -> dict:
"""simple docstrin... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowercase__ = {
"""configuration_gpt_neo""": ["""GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoConfig""", """GPTNeoOnnxConfig"""],
}... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Token... | 610 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCamelCase ( A__ ... | 610 |
"""simple docstring"""
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be chec... | 610 | 1 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> np.array:
"""simple docstring"""
lowerCAmelCase_ : str ... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> float:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __Upp... | 610 | 1 |
"""simple docstring"""
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from to... | 610 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from... | 610 | 1 |
"""simple docstring"""
from __future__ import annotations
def __lowerCamelCase ( __UpperCamelCase ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Any = [True] * limit
lowerCAmelCase_ : Optional[Any] = False
lowerCAmelCase_ : ... | 610 |
"""simple docstring"""
from typing import Any
def __lowerCamelCase ( __UpperCamelCase ) -> list[Any]:
"""simple docstring"""
if not input_list:
return []
lowerCAmelCase_ : Any = [input_list.count(__UpperCamelCase ) for value in input_list]
lowerCAme... | 610 | 1 |
"""simple docstring"""
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class __lowerCamelCase ( A__ ):
'''simple docstring'''
a_ : List[str] = """"""
a_ ... | 610 |
"""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 impo... | 610 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from... | 610 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"""configuration... | 610 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu... | 610 |
"""simple docstring"""
lowercase__ = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
lowercase__ = [{"""type""": """code""", """content""": INSTALL_CONTENT}... | 610 | 1 |
"""simple docstring"""
import csv
import tweepy
# Twitter API credentials
lowercase__ = """"""
lowercase__ = """"""
lowercase__ = """"""
lowercase__ = """"""
def __lowerCamelCase ( __UpperCamelCase ) -> None:
"""simple docstring"""
lowerCAmel... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 610 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowerCamelCase ( metaclass=A__ ):
'''simple docstring'''
a_ : Optional[Any] = ["""speech"""]
def __init__( self : int , *a_ : int , **a_ : ... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> tuple[int, int]:
"""simple docstring"""
try:
lowerCAmelCase_ : Tuple = float(__UpperCamelCase )
except ValueError:
raise ValueError("Please enter a valid number" )
lowerCAmelCa... | 610 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> int:
"""simple docstring"""
return 1 if input_a == input_a else 0
def __lowerCamelCase ( ) -> None:
"""simple docstring"""
assert xnor_gate(0 , 0 ) ==... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowercase__ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5OnnxConfig"""],
}
... | 610 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttent... | 610 | 1 |
"""simple docstring"""
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
lowercase__ = logging.getLogger(__name__)
class __lowerCamelCase ( A__ ):
'... | 610 |
"""simple docstring"""
import math
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
lowerCAmelCase_ : Any = f'''Input value of [number={number}] must be an integer'''
... | 610 | 1 |
"""simple docstring"""
import numpy
# List of input, output pairs
lowercase__ = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowercase__ = (((515, 22, 13), 555), ((61, 35, 49), 150))
lowercase__ = [2, 4, 1, 5]
lowercas... | 610 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import Tenso... | 610 | 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 impo... | 610 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
def lowerCamelCase ( self ... | 610 | 1 |
"""simple docstring"""
from __future__ import annotations
import pandas as pd
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Dict = [0] * no_of_processes
lowerCAmel... | 610 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 610 | 1 |
"""simple docstring"""
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization i... | 610 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCamelCase ... | 610 | 1 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""vocab_file""": """vocab.json""",
"""tokenizer_... | 610 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
lowercase__ = re.compile(r"""([a-z\d])([A-Z])""")
lowercase__ = re.compile(r"""(?<!_)_(?!_)""")
lowercase__ = re.compile(r"""(_{2,})""")
lowerc... | 610 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
lowercase__ = """\
"""
lowercase__ = """
Perplexity (PPL) is one of the most common metrics ... | 610 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerCamelCase ( A__ , A__ ):
'''simple docstring'''
@register_to_config
def __init__( self : ... | 610 | 1 |
"""simple docstring"""
lowercase__ = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
lowercase__ = [{"""type""": """code""", """content""": INSTALL_CONTENT}... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> str:
"""simple docstring"""
return "".join([hex(__UpperCamelCase )[2:].zfill(2 ).upper() for byte in list(__UpperCamelCase )] )
def __lowerCamelCase ( __UpperCamelCase ) -> byte... | 610 | 1 |
"""simple docstring"""
import math
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
lowerCAmelCase_ : Any = f'''Input value of [number={number}] must be an integer'''
... | 610 |
"""simple docstring"""
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_DOCSTRING,
B... | 610 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 610 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase__ = {"""UserAgent""": UserAgent().random}
def __lowerCamelCase ( __UpperCamelCase ) -> dict:
"""simple docstrin... | 610 | 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 e... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Token... | 610 | 1 |
"""simple docstring"""
lowercase__ = {
"""A""": """.-""", """B""": """-...""", """C""": """-.-.""", """D""": """-..""", """E""": """.""", """F""": """..-.""", """G""": """--.""",
"""H""": """....""", """I""": """..""", """J""": """.---""", """K""": """-.-""", """L""": """.-..""", """M""": """--"... | 610 |
"""simple docstring"""
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be chec... | 610 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
class __lowerCamelCase ( A__ ):
'''simple docstring'''
a_ : List[Any] = """bert-generation"""
def __init__( self : Dict , a_ : int=5_03_58 , a_ : ... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> float:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __Upp... | 610 | 1 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,... | 610 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from... | 610 | 1 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerCamelCase ( A__ , A__ ):
'''simple docstring'''
@register_to_config
def __init__( self : ... | 610 |
"""simple docstring"""
from typing import Any
def __lowerCamelCase ( __UpperCamelCase ) -> list[Any]:
"""simple docstring"""
if not input_list:
return []
lowerCAmelCase_ : Any = [input_list.count(__UpperCamelCase ) for value in input_list]
lowerCAme... | 610 | 1 |
"""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_funnel import FunnelTokenizer
lowercase__ = logging.get_logger(__name__)
lowe... | 610 |
"""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 impo... | 610 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = ... | 610 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"""configuration... | 610 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""Salesforce/blip-vqa-base""": """https://huggingface.co/Salesforce/blip-vqa-... | 610 |
"""simple docstring"""
lowercase__ = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
lowercase__ = [{"""type""": """code""", """content""": INSTALL_CONTENT}... | 610 | 1 |
"""simple docstring"""
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
lowercase__ = {
"""User-Agent""": """Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"""
""" (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 ... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 610 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Token... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> tuple[int, int]:
"""simple docstring"""
try:
lowerCAmelCase_ : Tuple = float(__UpperCamelCase )
except ValueError:
raise ValueError("Please enter a valid number" )
lowerCAmelCa... | 610 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> int:
"""simple docstring"""
return 1 if input_a == input_a else 0
def __lowerCamelCase ( ) -> None:
"""simple docstring"""
assert xnor_gate(0 , 0 ) ==... | 610 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/config.json""",
# See all XGLM models ... | 610 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttent... | 610 | 1 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __lowerCamelCase ... | 610 |
"""simple docstring"""
import math
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
lowerCAmelCase_ : Any = f'''Input value of [number={number}] must be an integer'''
... | 610 | 1 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> Optional[An... | 610 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import Tenso... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> bool:
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Validate that next vertex is not already in pat... | 610 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
def lowerCamelCase ( self ... | 610 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transf... | 610 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowercase__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable... | 610 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCamelCase ... | 610 | 1 |
"""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.activations import gelu_new, gelu_python, get_activation
@require_torch
class __lowerCamelCase ... | 610 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
lowercase__ = re.compile(r"""([a-z\d])([A-Z])""")
lowercase__ = re.compile(r"""(?<!_)_(?!_)""")
lowercase__ = re.compile(r"""(_{2,})""")
lowerc... | 610 | 1 |
"""simple docstring"""
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowercase__ = """src/transformers"""
# This i... | 610 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerCamelCase ( A__ , A__ ):
'''simple docstring'''
@register_to_config
def __init__( self : ... | 610 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class __lowerCamelCase :
'''simple docstring'''
a_... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> str:
"""simple docstring"""
return "".join([hex(__UpperCamelCase )[2:].zfill(2 ).upper() for byte in list(__UpperCamelCase )] )
def __lowerCamelCase ( __UpperCamelCase ) -> byte... | 610 | 1 |
"""simple docstring"""
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be chec... | 610 |
"""simple docstring"""
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_DOCSTRING,
B... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
"""to... | 610 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase__ = {"""UserAgent""": UserAgent().random}
def __lowerCamelCase ( __UpperCamelCase ) -> dict:
"""simple docstrin... | 610 | 1 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
)
lowercase__ =... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Token... | 610 | 1 |
"""simple docstring"""
import os
import time
import numpy as np
import onnxruntime as ort
lowercase__ = """1"""
lowercase__ = """0"""
lowercase__ = """1"""
lowercase__ = ort.SessionOptions()
lowercase__ = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print("""Create infe... | 610 |
"""simple docstring"""
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be chec... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase = 4000000 ) -> int:
"""simple docstring"""
lowerCAmelCase_ : Tuple = []
lowerCAmelCase_ , lowerCAmelCase_ : Union[str, Any] = 0, 1
while b <= n:
if b % 2 == 0:
... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> float:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __Upp... | 610 | 1 |
"""simple docstring"""
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_con... | 610 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( ) -> int:
"""simple docstring"""
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
lowerCAmelCase_ : str ... | 610 |
"""simple docstring"""
from typing import Any
def __lowerCamelCase ( __UpperCamelCase ) -> list[Any]:
"""simple docstring"""
if not input_list:
return []
lowerCAmelCase_ : Any = [input_list.count(__UpperCamelCase ) for value in input_list]
lowerCAme... | 610 | 1 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy a... | 610 |
"""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 impo... | 610 | 1 |
"""simple docstring"""
lowercase__ = 8.3144598
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> float:
"""simple docstring"""
if temperature < 0:
raise Exception("Temperature cannot be less than 0 K" )
if molar_mass <= 0:
raise Exception("... | 610 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"""configuration... | 610 | 1 |
"""simple docstring"""
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
Distil... | 610 |
"""simple docstring"""
lowercase__ = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
lowercase__ = [{"""type""": """code""", """content""": INSTALL_CONTENT}... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
lowerCAmelCase_ : List[str] = [0] * len(__UpperCamelCase )
lowerCAmelCase_ : Tuple = []
lowerCAmelCase_ : Optional[int] = []... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 610 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> tuple[int, int]:
"""simple docstring"""
try:
lowerCAmelCase_ : Tuple = float(__UpperCamelCase )
except ValueError:
raise ValueError("Please enter a valid number" )
lowerCAmelCa... | 610 | 1 |
"""simple docstring"""
lowercase__ = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie_nutr": 4186.8,
"kilocalorie_nutr": 4186800.00,
"el... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> int:
"""simple docstring"""
return 1 if input_a == input_a else 0
def __lowerCamelCase ( ) -> None:
"""simple docstring"""
assert xnor_gate(0 , 0 ) ==... | 610 | 1 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
lowercase__ = re.compile(r"""([a-z\d])([A-Z])""")
lowercase__ = re.compile(r"""(?<!_)_(?!_)""")
lowercase__ = re.compile(r"""(_{2,})""")
lowerc... | 610 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttent... | 610 | 1 |
"""simple docstring"""
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
... | 610 |
"""simple docstring"""
import math
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
lowerCAmelCase_ : Any = f'''Input value of [number={number}] must be an integer'''
... | 610 | 1 |
"""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, SchedulerOutput
def... | 610 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import Tenso... | 610 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowercase__ = False
lowercase__ = True
lowercase__ = False
if __name__ == "__main__":
lowercase__ ... | 610 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
def lowerCamelCase ( self ... | 610 | 1 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class __lowerCamelCase ( A__ ):
'''simple docstring'''
def __init__( self : List[str] , a_ : Optional[Any] , a_ : Dict ):
super().__init__()
self.reg... | 610 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 610 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __lowerCamelCase ( __UpperCamelCase ) -> None:
"""simple docstring"""
lowerCAmelCase_ , lowerCAmelCase_ : List[str] ... | 610 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCamelCase ... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ = {
"""configuration_perceiver""": ["""PERCEIVER_PRETRAINED_CONFIG_ARCHIV... | 610 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
lowercase__ = re.compile(r"""([a-z\d])([A-Z])""")
lowercase__ = re.compile(r"""(?<!_)_(?!_)""")
lowercase__ = re.compile(r"""(_{2,})""")
lowerc... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : Tuple = 0
for ch in input_str:
lowerCAmelCase_ : Union[str, Any] = ord(__UpperCamelCase )
lowerCAmelCase_ : List... | 610 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerCamelCase ( A__ , A__ ):
'''simple docstring'''
@register_to_config
def __init__( self : ... | 610 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""huggingface/informer-tourism-monthly""": (
"""https://huggingface.co/hugg... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> str:
"""simple docstring"""
return "".join([hex(__UpperCamelCase )[2:].zfill(2 ).upper() for byte in list(__UpperCamelCase )] )
def __lowerCamelCase ( __UpperCamelCase ) -> byte... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"""configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TimesformerConfig"""],
}
try:
if not is_torch_av... | 610 |
"""simple docstring"""
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_DOCSTRING,
B... | 610 | 1 |
"""simple docstring"""
from __future__ import annotations
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> Optional[int]: # noqa: E741
"""simple docstring"""
while r - l > 1:
lowerCAmelCase_ : Any = ... | 610 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase__ = {"""UserAgent""": UserAgent().random}
def __lowerCamelCase ( __UpperCamelCase ) -> dict:
"""simple docstrin... | 610 | 1 |
"""simple docstring"""
from typing import Any
def __lowerCamelCase ( __UpperCamelCase ) -> list[Any]:
"""simple docstring"""
if not input_list:
return []
lowerCAmelCase_ : Any = [input_list.count(__UpperCamelCase ) for value in input_list]
lowerCAme... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Token... | 610 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if... | 610 |
"""simple docstring"""
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be chec... | 610 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> float:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __Upp... | 610 | 1 |
"""simple docstring"""
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("dataset_size" , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("input_in_memory_max_size" , ["default", 0, 100 * 2**20, 900 * 2**20] )
def __l... | 610 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from... | 610 | 1 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {"""vocab_file""": """vocab.... | 610 |
"""simple docstring"""
from typing import Any
def __lowerCamelCase ( __UpperCamelCase ) -> list[Any]:
"""simple docstring"""
if not input_list:
return []
lowerCAmelCase_ : Any = [input_list.count(__UpperCamelCase ) for value in input_list]
lowerCAme... | 610 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def __lowerCamelCase ( ) -> Generator[int, None, None]:
"""simple docstring"""
lowerCAmelCase_ : dict[int, int] = {}
lowerCAmelCase_ : int = 2
... | 610 |
"""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 impo... | 610 | 1 |
"""simple docstring"""
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def __lowerCamelCase ( __UpperCamelCase ) -> str:
"""simple docstring"""
return x + 2
class __lowerCamelCase ... | 610 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"""configuration... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> list:
"""simple docstring"""
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(__UpperCamelCase ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__(... | 610 |
"""simple docstring"""
lowercase__ = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
lowercase__ = [{"""type""": """code""", """content""": INSTALL_CONTENT}... | 610 | 1 |
"""simple docstring"""
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowercase__ = """\
@inproceedings{kakwani2020indicnlpsuite,
title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual La... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
if not is_torch_available():
... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> tuple[int, int]:
"""simple docstring"""
try:
lowerCAmelCase_ : Tuple = float(__UpperCamelCase )
except ValueError:
raise ValueError("Please enter a valid number" )
lowerCAmelCa... | 610 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
lowercase__ = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
"""https://h... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> int:
"""simple docstring"""
return 1 if input_a == input_a else 0
def __lowerCamelCase ( ) -> None:
"""simple docstring"""
assert xnor_gate(0 , 0 ) ==... | 610 | 1 |
"""simple docstring"""
import re
def __lowerCamelCase ( __UpperCamelCase ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : str = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.search(__UpperCamelCa... | 610 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttent... | 610 | 1 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
lowercase__ = """
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is the true positives and FN i... | 610 |
"""simple docstring"""
import math
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
lowerCAmelCase_ : Any = f'''Input value of [number={number}] must be an integer'''
... | 610 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
lowercase__ = logging.get_logger(__name__)
class __lowerCamelCase ( A__ ):
'''simple docstring'''
def __init__( self : List[s... | 610 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import Tenso... | 610 | 1 |
"""simple docstring"""
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import... | 610 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
def lowerCamelCase ( self ... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_avai... | 610 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 610 | 1 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<m... | 610 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCamelCase ... | 610 | 1 |
"""simple docstring"""
print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
| 610 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
lowercase__ = re.compile(r"""([a-z\d])([A-Z])""")
lowercase__ = re.compile(r"""(?<!_)_(?!_)""")
lowercase__ = re.compile(r"""(_{2,})""")
lowerc... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> Optional[Any]:
"""simple docstring"""
lowerCAmelCase_ : Any = [1]
for i in range(2 , __UpperCamelCase ):
factorials.append(factorials[-1] * i )
assert 0 <= k... | 610 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerCamelCase ( A__ , A__ ):
'''simple docstring'''
@register_to_config
def __init__( self : ... | 610 | 1 |
"""simple docstring"""
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> int:
"""simp... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> str:
"""simple docstring"""
return "".join([hex(__UpperCamelCase )[2:].zfill(2 ).upper() for byte in list(__UpperCamelCase )] )
def __lowerCamelCase ( __UpperCamelCase ) -> byte... | 610 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_... | 610 |
"""simple docstring"""
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_DOCSTRING,
B... | 610 | 1 |
"""simple docstring"""
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteSc... | 610 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase__ = {"""UserAgent""": UserAgent().random}
def __lowerCamelCase ( __UpperCamelCase ) -> dict:
"""simple docstrin... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase = False ) -> str:
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
lowerCAmelCase_ : List[str] = f'''Expected string as input, found {typ... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Token... | 610 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 610 |
"""simple docstring"""
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be chec... | 610 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> float:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __Upp... | 610 | 1 |
"""simple docstring"""
# Algorithm for the pigeonhole sorting
def __lowerCamelCase ( __UpperCamelCase ) -> List[str]:
"""simple docstring"""
lowerCAmelCase_ : int = min(__UpperCamelCase ) # min() finds the minimum value
lowerCAmelCase_ : int ... | 610 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from... | 610 | 1 |
"""simple docstring"""
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowercase__ = datasets.load_iris()
lowercase__ = np.array(data["""data"""])
lowercase__ = np.array(data["""target"""])
lowercase_... | 610 |
"""simple docstring"""
from typing import Any
def __lowerCamelCase ( __UpperCamelCase ) -> list[Any]:
"""simple docstring"""
if not input_list:
return []
lowerCAmelCase_ : Any = [input_list.count(__UpperCamelCase ) for value in input_list]
lowerCAme... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> tuple[float, float]:
"""simple docstring"""
if not len(__UpperCamelCase ) == len(__UpperCamelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] ==... | 610 |
"""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 impo... | 610 | 1 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers... | 610 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"""configuration... | 610 | 1 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ = argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
parser.add_argument("... | 610 |
"""simple docstring"""
lowercase__ = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
lowercase__ = [{"""type""": """code""", """content""": INSTALL_CONTENT}... | 610 | 1 |
"""simple docstring"""
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
lowercase__ = logging.get_logger(__nam... | 610 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 610 | 1 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> bool:
"""simple docstring"""
return str(__UpperCamelCase ) == str(__UpperCamelCase )[::-1]
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
retur... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> tuple[int, int]:
"""simple docstring"""
try:
lowerCAmelCase_ : Tuple = float(__UpperCamelCase )
except ValueError:
raise ValueError("Please enter a valid number" )
lowerCAmelCa... | 610 | 1 |
"""simple docstring"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __lowerCamelCase ( __UpperCamelCase ... | 610 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> int:
"""simple docstring"""
return 1 if input_a == input_a else 0
def __lowerCamelCase ( ) -> None:
"""simple docstring"""
assert xnor_gate(0 , 0 ) ==... | 610 | 1 |
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