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 |
|---|---|---|---|---|
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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
ViltF... | 82 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase = 0 ):
"""simple docstring"""
lowerCAmelCase__ : Dict = length or len(__lowercase )
lowerCAmelCase__ : Dict = False
for i in range(length - 1 ):
... | 37 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 0 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
SCREAMING_SNAKE_CASE_: Tuple ='\nimport os\n'
SCREAMING_SNAKE_CASE_: Any ='\ndef foo():\n import os\n return False\n'
SCREAMING_SNAKE_CASE_: List[str] ='\ndef foo():\n def bar():\n... | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 0 |
from __future__ import annotations
from collections.abc import Callable
_SCREAMING_SNAKE_CASE = list[list[float | int]]
def lowercase( UpperCamelCase_ , UpperCamelCase_ ) -> Matrix:
'''simple docstring'''
UpperCamelCase = len(__lowercase )
UpperCamelCase... | 343 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 0 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
lowerCAmelCase : Tuple = logging.get_logger(__name__)
class __lowercase ( UpperCAmelCase_ ):
"""simple docstring"""
def __init__( self : List[Any] , *lowerCAmelCa... | 13 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 0 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class UpperCamelCase ( UpperCAmelCase_ , UpperCAmelCase_ ):
@register_to_config
def __init__( self, *,
l... | 69 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
S... | 28 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase ={"""configuration_vit_msn""": ["""VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMSNConfig"""]}
try:
if not is_torch_available():
raise OptionalDependency... | 287 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 0 |
import os
import time
import numpy as np
import onnxruntime as ort
_UpperCAmelCase : List[str] = """1"""
_UpperCAmelCase : Optional[int] = """0"""
_UpperCAmelCase : Tuple = """1"""
_UpperCAmelCase : Optional[Any] = ort.SessionOptions()
_UpperCAmelCas... | 50 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 0 |
def _A ( _lowercase ) -> int:
"""simple docstring"""
if not isinstance(__lowercase , __lowercase ):
raise TypeError('only integers accepted as input' )
else:
__UpperCamelCase = str(abs(__lowercase ) )
... | 310 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 0 |
def __a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> str:
'''simple docstring'''
if not isinstance(__lowercase , __lowercase ):
raise ValueError('''iterations must be defined as integers''' )
if not isinstance(__lowercase , ... | 333 |
'''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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 0 |
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoModelForMaskedLM,
... | 82 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing impor... | 319 | 0 |
'''simple docstring'''
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_... | 37 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon... | 319 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTester... | 1 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_blip""": [
"""BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BlipCo... | 343 |
'''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 = {
'''Yi... | 319 | 0 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMSchedule... | 13 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__UpperCamelCase = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''EncodecConfig''',
],
... | 69 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE ( metaclass=UpperCAmelCase_ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = ["""keras_nlp"""]
def __init__( self : Optional[int] , ... | 28 |
'''simple docstring'''
import heapq
import sys
import numpy as np
UpperCamelCase = tuple[int, int]
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] ) -> str:
'''simple ... | 319 | 0 |
def _a ( lowerCamelCase, lowerCamelCase, lowerCamelCase ):
def count_of_possible_combinations(lowerCamelCase ) -> int:
if target < 0:
return 0
if target == 0:
return 1
return sum(count_of_possible_combinations(target - item ) for item in array )
return count_of_poss... | 287 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int:
A: Any = 1
A: Optional[Any] = 0
for divide_by_number in range(__lowercase , digit + 1 ):
A: li... | 319 | 0 |
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.u... | 50 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 0 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_av... | 310 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 0 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class A_ :
'''simple docstring'''
a__ = None
def lowerCAmelCase_ (self ) -> Union[str, Any]:
__UpperCAmelCase = sel... | 333 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 0 |
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _UpperCAmelCase ( snake_case , snake_case , snake_case , snake_case ):
"""simple docstring"""
_lowerCAmelCase = s.rsplit(__lowercase , __lowerc... | 82 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import ... | 37 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_ut... | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 0 |
import os
from collections.abc import Iterator
def lowercase( UpperCamelCase_ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(__lowercase ):
UpperCamelCase = [d for d in dir_names if d != '''scripts''' and d[0] not in '''.... | 343 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def A_ ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ):
for nxt, d in grap... | 13 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , U... | 69 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 0 |
'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils im... | 28 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 0 |
import os
import platform
import sys
_lowerCamelCase ="""3"""
print("""Python version:""", sys.version)
print("""OS platform:""", platform.platform())
print("""OS architecture:""", platform.machine())
try:
import torch
print("""Torch version:""", torch.__version__)
print("""Cuda availabl... | 287 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 0 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class lowerCAmelCase ( UpperCAmelCase_ ):
UpperCAmelCase__ = ... | 50 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 0 |
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,
DistilBertForMa... | 310 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 0 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
A_ : int = ['small', 'medium', 'large']
A_ : int = 'lm_head.decoder.weight'
A_ : Optional[Any] = 'lm_head.weight'
def __a ( SCREAMING_SNAKE_CASE , SCREAMIN... | 333 |
'''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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""facebook/vit-mae-base""": """https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json""",
# See all ViT MAE models at https://huggingface.co/... | 82 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing impor... | 319 | 0 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
_lowerCAmelCase = '''\
@inproceedings{kakwani2020indicnlpsuite,
title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multili... | 37 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon... | 319 | 0 |
'''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 PegasusTokenizer
el... | 1 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 | 0 |
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE_ ( metaclass=UpperCAmelCase_ ):
__lowerCAmelCase = ["""flax"""]
def __init__( self : Any , *lowerCamelCase_ : Tuple , **lowerCamelCase_ : int ):
"""simple docstring"""
... | 343 |
'''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 = {
'''Yi... | 319 | 0 |
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
lowerCAmelCase : str = collections.namedtuple("""_Datasets""", ["""tra... | 13 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 0 |
"""simple docstring"""
from math import sqrt
def UpperCAmelCase ( UpperCAmelCase ) -> int:
snake_case_ = 0
for i in range(1 , int(sqrt(__lowercase ) + 1 ) ):
if n % i == 0 and i != sqrt(__lowercase ):
total += i + n... | 69 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 0 |
'''simple docstring'''
def __lowerCamelCase ( A__ , A__ ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def __lowerCamelCase ( ) -> None:
"""simple docstring"""
assert or_ga... | 28 |
'''simple docstring'''
import heapq
import sys
import numpy as np
UpperCamelCase = tuple[int, int]
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] ) -> str:
'''simple ... | 319 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECKING:
... | 287 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int:
A: Any = 1
A: Optional[Any] = 0
for divide_by_number in range(__lowercase , digit + 1 ):
A: li... | 319 | 0 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_UpperCAmelCase : str = False
try:
_UpperCAmelCase ... | 50 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 0 |
import math
import unittest
def _A ( _lowercase ) -> bool:
"""simple docstring"""
assert isinstance(__lowercase , __lowercase ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2... | 310 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 0 |
A_ : Any = {str(digit): digit**5 for digit in range(10)}
def __a ( SCREAMING_SNAKE_CASE ) -> int:
'''simple docstring'''
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(__lowercase ) )
def __a ( ) -> int:
... | 333 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 0 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _UpperCAmelCase ( snake_case , snake_case , snake_case ):
"""simple docstring"""
_lowerCAmelCase = ... | 82 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Mobile... | 37 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datase... | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 0 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ ):
def __init__( self : Union[str, Any] , *lowerCamelCase_ : List[str] ... | 343 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 0 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__ver... | 13 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase ( UpperCAmelCase ) -> list[int]:
snake_case_ = [True] * limit
snake_case_ = False
snake_case_ = False
snake_case_ = True
for i ... | 69 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 0 |
'''simple docstring'''
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.util... | 28 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 0 |
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_tokenization_common import TokenizerTesterMixin
i... | 287 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 0 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_pr... | 50 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 0 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOut... | 310 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def __a ( SCREAMING_SNAKE_CASE ) -> Optional[Any]:
'''simple docstring'''
__UpperCAmelCase = SwinConfig(... | 333 |
'''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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 0 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 82 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing impor... | 319 | 0 |
'''simple docstring'''
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import Batch... | 37 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon... | 319 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_: Optional[Any] ={
'configuration_vision_encoder_decoder': ['VisionEncoderDecode... | 1 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 | 0 |
import itertools
import os
import re
_SCREAMING_SNAKE_CASE = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
_SCREAMING_SNAKE_CASE = re.compile(r"""([a-z\d])([A-Z])""")
_SCREAMING_SNAKE_CASE = re.compile(r"""(?<!_)_(?!_)""")
_SCREAMING_SNAKE_CASE = re.compile(r"""(_{2,})""")
_SCR... | 343 |
'''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 = {
'''Yi... | 319 | 0 |
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
lowerCAmelCase : Optional[Any] = TypeVar("""T""")
class __lowercase ( Generic[T] ):
"""simple docstring"""
def __init__( self : Tuple , lowerCAmelCase__ : bool =... | 13 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 0 |
"""simple docstring"""
def UpperCAmelCase ( UpperCAmelCase ) -> list:
snake_case_ = len(__lowercase )
for i in range(1 , __lowercase ):
snake_case_ = collection[i]
snake_case_ = 0
snake_case_ ... | 69 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 0 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
_lowerCamelCase : Any = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def __lowerCamelCase ( ) -> Union[str, Any]:
"""simple docstring"""
UpperCamelC... | 28 |
'''simple docstring'''
import heapq
import sys
import numpy as np
UpperCamelCase = tuple[int, int]
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] ) -> str:
'''simple ... | 319 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A__ ( UpperCAmelCase_):
@staticmethod
@abstractmethod
def UpperCamelCase__ ( __magic_name__ ):
raise NotImplementedError()
@abstractmethod
def UpperCamelCase... | 287 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int:
A: Any = 1
A: Optional[Any] = 0
for divide_by_number in range(__lowercase , digit + 1 ):
A: li... | 319 | 0 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase ) -> str:
if "model" in orig_key:
lowerCamelCase__ : List[Any] = orig_key.replace('model.' , '' )
if "norm1" in orig_key:
... | 50 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 0 |
import math
from datetime import datetime, timedelta
def _A ( _lowercase ) -> datetime:
"""simple docstring"""
__UpperCamelCase = year % 19
__UpperCamelCase = year % 4
__UpperCamelCase = year % 7
__Upper... | 310 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 0 |
from manim import *
class A_ ( UpperCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase_ (self ) -> Union[str, Any]:
__UpperCAmelCase = Rectangle(height=0.5 , width=0.5 )
__UpperCAmelCase = Rectangle(height=0.46 , w... | 333 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 0 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class __lowerCAmelCase :
def __init__( self , _snake_case , _snake_case , _snake_case , _snake_case , _snake_case , _snake_case=0.2 , _snake_case=0.2 ):
... | 82 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 37 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_: Any ={
'configuration_upernet': ['UperNetConfig'],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
... | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 0 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_tokeni... | 343 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 0 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYaaag... | 13 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class UpperCamelCase ( unittest.TestCase ):
... | 69 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 0 |
'''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 i... | 28 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 0 |
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class A__ :
def __init__( self , __magic_name__ ):
if isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE... | 287 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 0 |
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_table,
)
from .np_formatter import NumpyForm... | 50 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 0 |
from __future__ import annotations
__snake_case = tuple[int, int, int]
__snake_case = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
__snake_case = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
# -------------------------- default selectio... | 310 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 0 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
A_ : Dict = 3
def __a ( SCREAMING_SNAKE_CASE ) -> int:
'''simple docstring'''
print('''Generating primitive root of p''' )
while... | 333 |
'''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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 0 |
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 as np
from .import_utils im... | 82 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing impor... | 319 | 0 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowerCAmelCase_( unittest.TestCase ):
'''simple docstring'''
def UpperCAmelCase_ ( self ) -> ... | 37 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon... | 319 | 0 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available()... | 1 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if... | 319 | 0 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class SCREAMING_SNAKE_CASE_ :
def __init__( self : Tuple ):
"""simple docstring"""
UpperCamelCase = ''''''
UpperCamelCase = ''''''
UpperCamelCase = []
... | 343 |
'''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 = {
'''Yi... | 319 | 0 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.pat... | 13 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 0 |
"""simple docstring"""
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__UpperCamelCase = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__UpperCamelCase = [file for ... | 69 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 0 |
'''simple docstring'''
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( UpperCAmelCase_ ):
"""simple docstring"""
_SCREAMING_SNAKE_CAS... | 28 |
'''simple docstring'''
import heapq
import sys
import numpy as np
UpperCamelCase = tuple[int, int]
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] ) -> str:
'''simple ... | 319 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCa... | 287 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int:
A: Any = 1
A: Optional[Any] = 0
for divide_by_number in range(__lowercase , digit + 1 ):
A: li... | 319 | 0 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDic... | 50 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 0 |
from collections import Counter
from timeit import timeit
def _A ( _lowercase = "" , ) -> bool:
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values() ) < 2
def _A ( ... | 310 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any:
A: Any = [x.strip() for x in open(__lowercase ... | 319 | 0 |
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCri... | 333 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list:
A: Dict = length or len(__lowercase )
A: Dict = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 319 | 0 |
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 ( UpperCAmelCase_ ... | 82 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 319 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase = 1000000 ):
"""simple docstring"""
lowerCAmelCase__ : Optional[Any] = limit + 1
lowerCAmelCase__ : List[Any] = [0] * limit
for first_term in range(1 , __lowercase ... | 37 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 319 | 0 |
'''simple docstring'''
import functools
def lowerCAmelCase_ ( snake_case_ : List[str] , snake_case_ : Tuple ) -> int:
'''simple docstring'''
if not isinstance(__lowercase , __lowercase ) or not all(isinstance(__lowercase , __lowercase ) fo... | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
... | 319 | 0 |
def lowercase( UpperCamelCase_ ) -> str: # noqa: E741
'''simple docstring'''
UpperCamelCase = len(__lowercase )
UpperCamelCase = 0
UpperCamelCase = [0] * n
UpperCamelCase = [False] * n
UpperCamelCase = [False] * n
def dfs(UpperCamelC... | 343 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
raise TypeError('''only integers accepted as input''' )
else:
A: str = str(abs(__lowercase ) ... | 319 | 0 |
from numpy import exp, pi, sqrt
def A_ ( _UpperCAmelCase , _UpperCAmelCase = 0.0 , _UpperCAmelCase = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 13 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Excepti... | 319 | 0 |
"""simple docstring"""
import re
def UpperCAmelCase ( UpperCAmelCase ) -> str:
if len(re.findall('[ATCG]' , __lowercase ) ) != len(__lowercase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ... | 69 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 319 | 0 |
'''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 ut... | 28 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 0 |
def _a ( ):
return [list(range(1000 - i, -1000 - i, -1 ) ) for i in range(1000 )]
_lowerCamelCase =generate_large_matrix()
_lowerCamelCase =(
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[[3, 2], [1, 0]],
[[7, 7, 6]],
[[7, 7, 6], [-1,... | 287 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor... | 319 | 0 |
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase = 400_0000 ) -> int:
lowerCamelCase__ : Union[str, Any] = []
lowerCamelCase__ : Union[str, Any] = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__lowercase )
lowerCamelCase__... | 50 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __... | 319 | 0 |
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__snake_case = logging.get_logger(__name__)
def _A ( _lowercase ) -> List[int]:
"""simple docstring"""
if isinstance(__lowe... | 310 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 0 |
from __future__ import annotations
import math
def __a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> list:
'''simple docstring'''
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
rais... | 333 |
'''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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 319 | 0 |
"""simple docstring"""
__snake_case = range(2, 20 + 1)
__snake_case = [10**k for k in range(ks[-1] + 1)]
__snake_case = {}
def A_ ( _lowerCAmelCase : List[str], _lowerCAmelCase : Optional[Any], _lowerCAmelCase : Optional[int], _lowerCAmelCase : Union[s... | 320 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.co/microsoft/unisp... | 320 | 1 |
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