code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_outp... | 254 |
'''simple docstring'''
import math
import os
import sys
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Any = """"""
try:
with open(lowerCAmelCase__ , """rb""" ) as binary_file:
_... | 254 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...te... | 254 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_in... | 254 | 1 |
'''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,
)
... | 254 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...te... | 254 | 1 |
'''simple docstring'''
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class _A ( __SCREAMING_SNAKE_CASE ):
def __init__( self , __UpperCAmelCase="" , __UpperCAmelCase="train" ) -> Union[str, Any]:
'''si... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Tr... | 254 | 1 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except O... | 254 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : Optional[str] = None ):
... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : str = """"""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
... | 254 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def ... | 254 | 1 |
'''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _A ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
_SCREAMING_SNAKE_CASE ... | 254 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
_UpperCamelCase = {'''vocab_file''': '''vocab.txt''', '''tokenizer_f... | 254 | 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,
B... | 254 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowercase_ ( lowerCAmelCase__ : Union[str, Any] ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = FileLock(str(tmpdi... | 254 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...te... | 254 |
'''simple docstring'''
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
_UpperCamelCase = ver... | 254 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_mctct''': ['''MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MCTCTConfig'''],
'''feature_extraction_mctct''': [... | 254 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_UpperCamelCase = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
_UpperCamelCase = '''
Args:
... | 254 | 1 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if n... | 254 | 1 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def lowercase_ ( lowerCAmelCase__ : str ):
"... | 254 | 1 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, T... | 254 |
'''simple docstring'''
import qiskit
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : Union[str, Any] = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : list[int] ):
"""simple docstring"""
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__UpperCAmelCase : Optional[Any] = sum(lowerCAmel... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : list[list[int]] = [[0 for _ in range(lowerCAmelCase__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__UpperCAmelCa... | 254 | 1 |
'''simple docstring'''
import numpy as np
class _A :
def __init__( self ) -> List[str]:
'''simple docstring'''
__UpperCAmelCase : Optional[int] = (0, 0)
__UpperCAmelCase : Dict = None
__UpperCAmelCase : int = 0
... | 254 |
'''simple docstring'''
_UpperCamelCase = '''
# 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
'''
_UpperCamelCase = [{'''type''': '''code''', '''content''': INSTALL... | 254 | 1 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CON... | 254 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 254 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.num... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_UpperCamelCase = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Brid... | 254 | 1 |
'''simple docstring'''
import math
import random
def lowercase_ ( lowerCAmelCase__ : float , lowerCAmelCase__ : bool = False ):
"""simple docstring"""
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initi... | 254 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.vers... | 254 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from di... | 254 |
'''simple docstring'''
from pathlib import Path
import fire
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : List[str] = Path(lowerCAmelCase... | 254 | 1 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e ... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int = 50 ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_l... | 254 | 1 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenizat... | 254 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenizat... | 254 | 1 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
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/... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_t... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : dict ):
"""simple docstring"""
__UpperCAmelCase : Dict = set()
# edges = list of graph's edges
__UpperCAmelCase : Dict = get_edges(lowerCAmelCase__ )
# While there ... | 254 |
'''simple docstring'''
import math
import os
import sys
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Any = """"""
try:
with open(lowerCAmelCase__ , """rb""" ) as binary_file:
_... | 254 | 1 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_UpperCamelCase = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Syst... | 254 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_in... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
if index == number_of_items:
... | 254 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...te... | 254 | 1 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
_UpperCamelCase = False
class _A ( u... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Tr... | 254 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class _A ( __SCREAMING_SN... | 254 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : Optional[str] = None ):
... | 254 | 1 |
'''simple docstring'''
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
... | 254 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def ... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int ):
"""simple docstring"""
if len(lowerCAmelCase__ ) != len(lowerCAmelCase__ ):
raise ValueError("""The length of ... | 254 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
_UpperCamelCase = {'''vocab_file''': '''vocab.txt''', '''tokenizer_f... | 254 | 1 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def lowercase_ ( lowerCAmelCase__ : Tuple , lowerCAmelCase__ : List[Any] , lowerCAmelCase__ : str , lowerCAmelCase__ : Tuple ):
"""simple docstring"""
... | 254 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowercase_ ( lowerCAmelCase__ : Union[str, Any] ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = FileLock(str(tmpdi... | 254 | 1 |
'''simple docstring'''
import math
import os
import sys
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Any = """"""
try:
with open(lowerCAmelCase__ , """rb""" ) as binary_file:
_... | 254 |
'''simple docstring'''
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
_UpperCamelCase = ver... | 254 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
_UpperCamelCase = list[list[float | int]]
def lowercase_ ( lowerCAmelCase__ : Matrix , lowerCAmelCase__ : Matrix ):
"""simple docstring"""
__Uppe... | 254 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_UpperCamelCase = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
_UpperCamelCase = '''
Args:
... | 254 | 1 |
'''simple docstring'''
from __future__ import annotations
_UpperCamelCase = list[list[int]]
# assigning initial values to the grid
_UpperCamelCase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if n... | 254 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import requ... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def lowercase_ ( lowerCAmelCase__ : str ):
"... | 254 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 254 |
'''simple docstring'''
import qiskit
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : Union[str, Any] = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum... | 254 | 1 |
'''simple docstring'''
import random
def lowercase_ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : List[str] ):
"""simple docstring"""
__UpperCAmelCase : List[str] = a[left_index]
__UpperCAmelCase ... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : list[list[int]] = [[0 for _ in range(lowerCAmelCase__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__UpperCAmelCa... | 254 | 1 |
'''simple docstring'''
_UpperCamelCase = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609_344,
"knot": 1.852,
}
_UpperCamelCase = {
"km/h": 1.0,
"m/s": 0.277_777_778,
"mph": 0.621_371_192,
"knot": 0.539_956_803,
}
def lowercase_ ( lowerCAmelCase... | 254 |
'''simple docstring'''
_UpperCamelCase = '''
# 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
'''
_UpperCamelCase = [{'''type''': '''code''', '''content''': INSTALL... | 254 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_UpperCamelCase = {
'''configuration_pix2struct''': [
'''PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Pix2St... | 254 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 254 | 1 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : Optional[str] = None ):
... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_UpperCamelCase = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Brid... | 254 | 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 imp... | 254 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.vers... | 254 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config imp... | 254 |
'''simple docstring'''
from pathlib import Path
import fire
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : List[str] = Path(lowerCAmelCase... | 254 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int = 50 ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_l... | 254 | 1 |
'''simple docstring'''
_UpperCamelCase = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
_UpperC... | 254 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenizat... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError("""both inputs must be positive integers""" )
__UpperCAmelCase : ... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_t... | 254 | 1 |
'''simple docstring'''
import math
import sys
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Union[str, Any] = """"""
try:
with open(lowerCAmelCase__ , """rb""" ) as binary_file:
... | 254 |
'''simple docstring'''
import math
import os
import sys
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Any = """"""
try:
with open(lowerCAmelCase__ , """rb""" ) as binary_file:
_... | 254 | 1 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_Upper... | 254 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_in... | 254 | 1 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/config.json''... | 254 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...te... | 254 | 1 |
'''simple docstring'''
import math
import unittest
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
assert isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Tr... | 254 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
... | 254 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : Optional[str] = None ):
... | 254 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetectio... | 254 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def ... | 254 | 1 |
'''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 _A ( __... | 254 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
_UpperCamelCase = {'''vocab_file''': '''vocab.txt''', '''tokenizer_f... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int = 100 ):
"""simple docstring"""
__UpperCAmelCase : Dict = 0
__UpperCAmelCase : Optional[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
... | 254 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowercase_ ( lowerCAmelCase__ : Union[str, Any] ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = FileLock(str(tmpdi... | 254 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils im... | 254 |
'''simple docstring'''
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
_UpperCamelCase = ver... | 254 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
_UpperCamelCase = {'''vocab_file''': '''vocab.txt''', '''tokenizer_f... | 254 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_UpperCamelCase = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
_UpperCamelCase = '''
Args:
... | 254 | 1 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if n... | 254 | 1 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def lowercase_ ( lowerCAmelCase__ : np.ndarray , lowerCAmelCase__ : np.ndarray , lowerCAmelCase__ : np.ndarray , lowerCAmelCase__ : int ,... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def lowercase_ ( lowerCAmelCase__ : str ):
"... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
return str(lowerCAmelCase__ ) == str(lowerCAmelCase__ )[::-1]
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
... | 254 |
'''simple docstring'''
import qiskit
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : Union[str, Any] = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum... | 254 | 1 |
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, sha... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : list[list[int]] = [[0 for _ in range(lowerCAmelCase__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__UpperCAmelCa... | 254 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''nielsr/canine-s''': 2048,
}
# Unicode defines ... | 254 |
'''simple docstring'''
_UpperCamelCase = '''
# 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
'''
_UpperCamelCase = [{'''type''': '''code''', '''content''': INSTALL... | 254 | 1 |
'''simple docstring'''
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def ... | 254 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 254 | 1 |
'''simple docstring'''
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='''%(message)s''')
def lowercase_ ( lowerCAmelCase__ : np.ndarray ):
"""simple docstring"""
return input_arr... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_UpperCamelCase = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Brid... | 254 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
_UpperCamelCase = TypeVar('''T''')
_UpperCamelCase = TypeVar('''U''')
class _A ( Generic[T, U] ):
def __init__( self , ... | 254 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.vers... | 254 | 1 |
'''simple docstring'''
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
fro... | 254 |
'''simple docstring'''
from pathlib import Path
import fire
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : List[str] = Path(lowerCAmelCase... | 254 | 1 |
'''simple docstring'''
import unittest
from transformers import DonutProcessor
_UpperCamelCase = '''naver-clova-ix/donut-base'''
class _A ( unittest.TestCase ):
def __A ( self ) -> Optional[Any]:
'''simple docstring'''
__UpperCAmelCase ... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int = 50 ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_l... | 254 | 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, RegNetParam... | 254 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenizat... | 254 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_t... | 254 | 1 |
'''simple docstring'''
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...gener... | 254 |
'''simple docstring'''
import math
import os
import sys
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Any = """"""
try:
with open(lowerCAmelCase__ , """rb""" ) as binary_file:
_... | 254 | 1 |
'''simple docstring'''
import math
def lowercase_ ( lowerCAmelCase__ : float , lowerCAmelCase__ : float ):
"""simple docstring"""
if (
not isinstance(lowerCAmelCase__ , (int, float) )
or power_factor < -1
or power_fac... | 254 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_in... | 254 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''YituTech/c... | 254 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...te... | 254 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Tr... | 254 | 1 |
'''simple docstring'''
_UpperCamelCase = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
_UpperC... | 254 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : Optional[str] = None ):
... | 254 | 1 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_inf... | 254 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def ... | 254 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {'''configuration_vit_msn''': ['''VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMSNConfig''']}
try:
if not is_torch_available(... | 254 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
_UpperCamelCase = {'''vocab_file''': '''vocab.txt''', '''tokenizer_f... | 254 | 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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
... | 254 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowercase_ ( lowerCAmelCase__ : Union[str, Any] ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = FileLock(str(tmpdi... | 254 | 1 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase_ ( *lowerCAmelCase__ : List[Any] , lowerCAmelCase__ : Optional[Union[Dict, Any]] = None , lowerCAmelCase__ : str=True ,... | 254 |
'''simple docstring'''
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
_UpperCamelCase = ver... | 254 | 1 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowercase_ ( lowerCAmelCase__ : Union[str, Any] ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = FileLock(str(tmpdi... | 254 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_UpperCamelCase = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
_UpperCamelCase = '''
Args:
... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int = 1000 ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = -1
__UpperCAmelCase : Union[str, Any] = 0
for a in range(1 , n // 3 ):
# Solving the ... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if n... | 254 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def lowercase_ ( lowerCAmelCase__ : str ):
"... | 254 | 1 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class _A ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
@regi... | 254 |
'''simple docstring'''
import qiskit
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : Union[str, Any] = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum... | 254 | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelin... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : list[list[int]] = [[0 for _ in range(lowerCAmelCase__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__UpperCAmelCa... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : Tuple , lowerCAmelCase__ : str , lowerCAmelCase__ : Union[str, Any] , lowerCAmelCase__ : List[str] ):
"""simple docstring"""
global f # a global dp table for knapsack
if f[... | 254 |
'''simple docstring'''
_UpperCamelCase = '''
# 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
'''
_UpperCamelCase = [{'''type''': '''code''', '''content''': INSTALL... | 254 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import Pegas... | 254 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 254 | 1 |
'''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWit... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_UpperCamelCase = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Brid... | 254 | 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
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelC... | 254 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.vers... | 254 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_... | 254 |
'''simple docstring'''
from pathlib import Path
import fire
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : List[str] = Path(lowerCAmelCase... | 254 | 1 |
'''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 lowercase_ ( ... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int = 50 ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_l... | 254 | 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 _A :
_SCREAMING_SNAKE_CASE : List[str]
_SC... | 254 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenizat... | 254 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class _A :
def __init__( self , __UpperCAmelCase ) -> None:
'''simple docstring'''
__UpperCAmelCase : str = value
__UpperCAmelCase : ... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_t... | 254 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils impo... | 254 |
'''simple docstring'''
import math
import os
import sys
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Any = """"""
try:
with open(lowerCAmelCase__ , """rb""" ) as binary_file:
_... | 254 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...... | 254 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_in... | 254 | 1 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
_UpperCamelCase = datasets.utils.logging.get_logger(__name__)
@datacla... | 254 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...te... | 254 | 1 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_v... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Tr... | 254 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Tr... | 254 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , lowerCAmelCase__ : Optional[str] = None ):
... | 254 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as... | 254 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def ... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def lowercase_ ( lowerCAmelCase__ : str ):
"... | 254 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
_UpperCamelCase = {'''vocab_file''': '''vocab.txt''', '''tokenizer_f... | 254 | 1 |
'''simple docstring'''
import requests
def lowercase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Tuple = {"""Content-Type""": """application/json"""}
__UpperCAmelCase : Tuple ... | 254 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowercase_ ( lowerCAmelCase__ : Union[str, Any] ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = FileLock(str(tmpdi... | 254 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int = 3 , lowerCAmelCase__ : int = 7 , lowerCAmelCase__ : int = 1000000 ):
"""simple docstring"""
__UpperCAmelCase : Union[str, Any] = 0
__UpperCAmelCase : Union[... | 254 |
'''simple docstring'''
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
_UpperCamelCase = ver... | 254 | 1 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_in... | 254 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_UpperCamelCase = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
_UpperCamelCase = '''
Args:
... | 254 | 1 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def lowercase_ ( lowerCAmelCase__ : Any ):
"""simple docstring"""
def wrapper(*lowerCAmelC... | 254 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if n... | 254 | 1 |
'''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 _A ( unittest.TestCase ):
def __A ( self ) -> Optional[int]:
'''simple doc... | 254 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def lowercase_ ( lowerCAmelCase__ : str ):
"... | 254 | 1 |
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