code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_... | 144 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenization_m... | 144 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProces... | 429 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax... | 429 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case: str = {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}
try:
if not is_torch_available():
r... | 577 |
'''simple docstring'''
def _snake_case ( A_ : str , A_ : str ):
"""simple docstring"""
if not (isinstance(A_ , A_ ) and isinstance(A_ , A_ )):
raise ValueError("""longest_common_substring() takes two strings for inputs""" )
a_ : Optional[int... | 577 | 1 |
'''simple docstring'''
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
a : Dict = False
class SCREAMING_SNAKE_CASE__ ( unittest.Te... | 680 |
'''simple docstring'''
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
a : Dict = '''... | 680 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionPipeline,
UnCLIPIma... | 171 |
'''simple docstring'''
from math import sqrt
def lowerCAmelCase_ ( a : int = 1000000 ):
a__ = 0
a__ = 0
a__ = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest... | 394 | 0 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def a ( snake_case__: Dict ):
'''simple docstring'''
lowercase_ = {}
lowercase_ = job['''started_at''']
lowercase_ = j... | 409 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
... | 409 | 1 |
"""simple docstring"""
def lowercase_ ( _snake_case ,_snake_case ):
SCREAMING_SNAKE_CASE__ : Tuple = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
SCREAMING_SNAKE_CASE__ : List[Any] = n - k
# Calculate C(n,k)
... | 223 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
_low... | 565 | 0 |
"""simple docstring"""
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_f... | 135 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
... | 135 | 1 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import tor... | 107 | from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ... | 423 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( __lowerCAmelCase = 200 ) -> int:
'''simple docstring'''
lowerCamelCase__ =[1, 2, 5, 10, 20, 50, 100, 200]
lowerCamelCase__ =[0] * (pence + 1)
lowerCamelCase__ =1 # base case: 1 way to make 0 pence
... | 132 | """simple docstring"""
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 132 | 1 |
"""simple docstring"""
import os
def lowerCAmelCase_ () -> List[str]:
a_ : List[Any] = os.path.join(os.path.dirname(_SCREAMING_SNAKE_CASE ) , "num.txt" )
with open(_SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(_SCREAMING_SNAKE_CASE ) for line i... | 473 | """simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class UpperCAmelCase__ ( __lowerCamelCase ):
"""simple docstring"""
lowerCAmelCase__ : Any = """Speech2TextFeatureExtractor"""
lowerCAmelCase__ : ... | 473 | 1 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
... | 712 |
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached... | 410 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerConfig"]}
t... | 611 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class a ( unittest.TestCase , __UpperCAmelC... | 611 | 1 |
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Tuple = logging.get_logger(__name__)
snake_case_ : Optional[int] = {
'''microsoft/xprophetnet-large-wiki100-cased''': (
... | 704 |
def A__ ( SCREAMING_SNAKE_CASE_ ) -> bool:
lowerCamelCase : Optional[Any] =[int(SCREAMING_SNAKE_CASE_ ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(SCREAMING_SNAKE_CASE_ ) == 4 and all(0 <= int(SCREAMING_SNAKE_CASE_ ) <= 2_5_4 for octet in octets )... | 262 | 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,
StableDiffusionXLImga... | 594 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowe... | 594 | 1 |
'''simple docstring'''
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,... | 701 |
'''simple docstring'''
class _A :
'''simple docstring'''
def __init__( self : List[Any] )-> List[str]:
snake_case__ : List[str] = """"""
snake_case__ : Dict = """"""
snake_case__ : Union[str, Any] ... | 172 | 0 |
from __future__ import annotations
def a_ ( __magic_name__ , __magic_name__ , __magic_name__ ) -> int | float:
"""simple docstring"""
if len(_SCREAMING_SNAKE_CASE ) == 0:
raise ValueError('''find_max() arg is an empty sequence''' )
... | 598 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {"""vocab... | 235 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_ut... | 254 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
UpperCamelCase__ = logging.ge... | 254 | 1 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _SCREAMING_SNAKE_CASE ( snake_case__... | 200 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Trai... | 659 | 0 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __lowerCAmelCase ... | 399 |
'''simple docstring'''
def __lowerCAmelCase ( snake_case__ ):
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(snake_case__ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('''doctest''').testmod()
| 399 | 1 |
from math import pi
def _snake_case (_snake_case : int , _snake_case : int) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 181 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json",
}
class SCREAMING_SNAKE... | 181 | 1 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.rob... | 60 |
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
__snake_case :Optional[int] = collections.namedtuple('''_Datasets''', ['''trai... | 60 | 1 |
from __future__ import annotations
import math
from collections.abc import Callable
def a__ ( A__, A__, A__, A__ = 1_0_0, ):
SCREAMING_SNAKE_CASE_ : Tuple = x_start
SCREAMING_SNAKE_CASE_ : Dict = fnc(A__ )
SCREAMING_SNAKE_CAS... | 101 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {'v... | 321 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMo... | 308 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowerCamelCase : List[str] = {
"""configuration_xlm""": ["""XLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMConfig""", """XLMOnnxConfig"""],
"""tok... | 308 | 1 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDatase... | 22 |
from __future__ import annotations
class lowerCAmelCase :
def __init__( self :Union[str, Any] , _lowercase :List[Any]=None ):
'''simple docstring'''
lowercase__ = data
lowercase__ = None
def __repr__( self :Dict ... | 655 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
... | 659 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_av... | 659 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 200 ) -> int:
'''simple docstring'''
snake_case_ = [1, 2, 5, 10, 20, 50, 100, 200]
snake_case_ = [0] * (pence + 1)
snake_case_ = 1 # base case: 1 way to make 0 pen... | 640 |
'''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
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMo... | 640 | 1 |
'''simple docstring'''
def _a ( _lowercase : str ):
'''simple docstring'''
__UpperCAmelCase : str = [int(_lowercase ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(_lowercase ) == 4 and all(0 <=... | 715 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _a ( _lowercase : int ):
'''simple docstring'''
__UpperCAmelCase : int = int(number**0.5 )
... | 266 | 0 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available()... | 123 |
"""simple docstring"""
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowercase__ : str = datasets.logging.get_logger(__name__)
lowercase__ : List[Any] ... | 123 | 1 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( snake_case__ ) -> bool:
__UpperCAmelCase =str(snake_case__ )
return len(snake_case__ ) == 9 and set(snake_case__ ) == set('''123456789''' )
def SCREAMING_SNAKE_CASE ( ) -> int | None:
for base_... | 142 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING... | 142 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokeniza... | 406 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'configuration_table_transformer': [
'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TableTransformerConfig',
'Ta... | 406 | 1 |
def _SCREAMING_SNAKE_CASE ( __lowercase : float , __lowercase : list[float] ) -> float:
"""simple docstring"""
if discount_rate < 0:
raise ValueError("""Discount rate cannot be negative""" )
if not cash_flows:
raise ValueError("""Cash flows l... | 199 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Enc... | 199 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
... | 69 |
'''simple docstring'''
import argparse
import os
import re
__snake_case : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
__snake_case : Optional[Any] = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
__snake_case : ... | 215 | 0 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : Optional[int] , _lowerCAmelCase : int , _lowerCAmelCase : Any , _lowerCAmelCase : Dict ) -> List[Any]:
global f # a global dp table for knapsack
if f[i][j] < 0:... | 528 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Tuple , _lowerCAmelCase : int , _lowerCAmelCase : Tuple ) -> Union[str, Any]:
# Return True if there is node that has not iterated.
Upp... | 528 | 1 |
import random
def SCREAMING_SNAKE_CASE ( UpperCAmelCase__ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = num - 1
_SCREAMING_SNAKE_CASE = 0
while s % 2 == 0:
_SCREAMING_SNAKE_CASE = s // 2
t += 1
for _ in range(5 ):
... | 605 |
"""simple docstring"""
from __future__ import annotations
import bisect
def _lowerCAmelCase ( lowerCamelCase__ : list[int], lowerCamelCase__ : int, lowerCamelCase__ : int = 0, lowerCamelCase__ : int = -1 ) -> int:
if hi < 0:
_SCREAMING_SNAKE_CASE :... | 572 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json",
"microsoft/markuplm-large": "https://huggingface.co/microsoft/ma... | 705 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
"RWKV/rwkv-4-169m-pile": "https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json",
"RWKV/rwkv-4-430m-pile": "https://huggingface.co/RWKV/rwkv-4-430m-pi... | 375 | 0 |
"""simple docstring"""
def _snake_case ( lowercase__ , lowercase__ ):
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / de... | 630 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def _SCREAMING_SNAKE_CASE ( a ) -> Tuple:
__A ... | 239 | 0 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case_ ( _a ):
"""simple docstring"""
__UpperCAmelCase =(CMStochasticIterativeScheduler,)
__UpperCAmelCase =... | 707 |
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,
... | 102 | 0 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .r... | 85 |
def lowerCAmelCase ( ) ->Dict:
"""simple docstring"""
__magic_name__ : Optional[int] = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
__magic_name__ : Optional[Any] = 6
__magic_name__ : Dict = 1
... | 154 | 0 |
from __future__ import annotations
def lowercase_ ( SCREAMING_SNAKE_CASE : list[int] , SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
snake_case__ : list[list[int]] =[]
snake_case__ : list[int] =[]
snake_case__ : Union[str, Any] =0
snake_case__ ... | 408 |
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
lowerCamelCase__ = '''\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang, Alex and S... | 408 | 1 |
'''simple docstring'''
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class _lowerCAmelCase ( __snake_case ):
"""simple docstring"""
snake_case_ = "M-CLIP"
def __init__( self : D... | 369 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowercase__ = "src/transformers"
# This is to make sure the trans... | 581 | 0 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def A__ ( _UpperCAmelCase : str , _UpperCAmelCase : Optional[int]=False ) -> int:
'''simple docstring'''
snake_case__ : Opt... | 150 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase = {
"""configuration_convbert""": ["""CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",... | 150 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = len(__UpperCAmelCase )
__SCREAMING_SNAKE_CASE = len(__UpperCAmelCase )
__SCREAMING_SNAKE_CASE ... | 109 |
from __future__ import annotations
import numpy as np
def __UpperCamelCase ( _lowerCAmelCase ) -> tuple[np.ndarray, np.ndarray]:
"""simple docstring"""
A , A : int = np.shape(_lowerCAmelCase )
if rows != columns:
A : Union[str, Any] = ... | 662 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json',
}
... | 711 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Nega... | 28 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaF... | 78 | '''simple docstring'''
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision... | 78 | 1 |
'''simple docstring'''
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
lowerCAmelCase = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=Non... | 551 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCAmelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Sau... | 551 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transfo... | 90 |
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
a = yaml.safe_load(
"\\nname: \"\"\nallow_empty: false\nallow_empty_text: true\nsubsections:\n - name: \"D... | 518 | 0 |
'''simple docstring'''
def A ( _UpperCAmelCase : int ) -> int:
'''simple docstring'''
__lowerCAmelCase : List[str] = 0
while num > 0:
digit_sum += num % 1_0
num //= 1_0
return digit_sum
def A ( _UpperCAmelCase : int... | 705 |
'''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 ...test_toke... | 123 | 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 r... | 415 |
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
A_ : str = WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])
def UpperCamelCase (lowercase_: Union[str, Any] ) ->... | 456 | 0 |
'''simple docstring'''
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 i... | 705 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, Swin... | 449 | 0 |
"""simple docstring"""
from __future__ import annotations
import bisect
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase = 0 , _lowerCamelCase = -1 ):
'''simple docstring'''
if hi < 0:
_lowerCAmelCase : Any = len(_A )
... | 259 |
"""simple docstring"""
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self ):
"""simple docstring"""
snake_case_ :Optional[Any] = 0
snake_case_ :Dict = 0
snake_case_ :Any = {}
... | 584 | 0 |
def _a ( SCREAMING_SNAKE_CASE_ : list[int] , SCREAMING_SNAKE_CASE_ : list[int] ):
__lowerCAmelCase = len(SCREAMING_SNAKE_CASE_ )
print("The following activities are selected:" )
# The first activity is always selected
__lowerCAmelCase ... | 552 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ = _LazyModule(__name__, globals()[... | 552 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_util... | 543 |
"""simple docstring"""
def a__ ( snake_case__ = 10_00 ) -> int:
lowerCamelCase , lowerCamelCase = 1, 1
lowerCamelCase = 2
while True:
lowerCamelCase = 0
lowerCamelCase = fa + fa
lowerCamelCase , lowerCamelCase = fa, f
... | 543 | 1 |
from math import sqrt
def _SCREAMING_SNAKE_CASE ( lowercase : int = 1_00_00_00 ):
'''simple docstring'''
lowerCamelCase_ = 0
lowerCamelCase_ = 0
lowerCamelCase_ = 42
while num_cuboids <= limit:
max_cuboid_size += 1
... | 708 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import GradientAccumulator, crea... | 651 | 0 |
'''simple docstring'''
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetV... | 444 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
lowerCAmelCase : Dict = """docs/source/en/_toctree.yml"""
def lowercase (_A ):
"""simple docstring"""
_lowerCAme... | 444 | 1 |
'''simple docstring'''
import unittest
from knapsack import knapsack as k
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : int ) -> Optional[Any]:
"""simple docstring"""
lowerCamelCase_ : Optional[int] = ... | 714 |
'''simple docstring'''
import random
def __snake_case (__UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ):
"""simple docstring"""
lowerCamelCase_ : List[str] = a[left_index]
lowerCamelCase_ : List[str] = left_index + 1
for j in range(le... | 418 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase_ : int = {'''processing_l... | 673 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 673 | 1 |
import numpy as np
def lowerCAmelCase ( lowerCAmelCase_ , lowerCAmelCase_ )-> Any:
return np.where(vector > 0 , A_ , (alpha * (np.exp(A_ ) - 1)) )
if __name__ == "__main__":
import doctest
doctest.testmod() | 710 |
def lowerCAmelCase ( lowerCAmelCase_ = 1_000_000 )-> int:
lowerCAmelCase_ : Dict = 1
lowerCAmelCase_ : List[Any] = 1
lowerCAmelCase_ : Optional[Any] = {1: 1}
for inputa in range(2 , lowerCAmelCase_ ):
lowerCAmelCase_ : Tuple = ... | 619 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : str = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
... | 44 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : str = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
... | 44 | 1 |
def UpperCAmelCase_ ( lowerCamelCase_ , lowerCamelCase_ ):
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(lowerCamelCase_ , x % y )
def UpperCAmelCase_ ( lowerCamelCase_ , lowerCamelCase_ ):
"""simple docstring"""
return (x * y) // greatest_co... | 712 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def UpperCAmelCase_ ( lowerCamelCase_ = 2_0_0_0_0_0_0 ):
"""simple docstring"""
lowerCAmelCase__ : list[int] = [0]
lowerCAmelCase__ : int
for idx in range(1 , ceil(sqrt(targ... | 568 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_av... | 101 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
A : Dict = get_logger(__name__)
A : Dict = R"\n Args:\n input_ids (`jnp.ndarray` of shape `(... | 636 | 0 |
'''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, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
fr... | 368 |
'''simple docstring'''
def snake_case_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
_snake_case = [0 for i in range(len(SCREAMING_SNAKE_CASE__ ) )]
# initialize interval's left pointer and right pointer
_snake_case , _snake_case = 0, 0
... | 368 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}
class lowerCAmelCase_ ( ... | 10 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase : Union[str, Any] = {"configuration_vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE... | 711 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Dict = logging.get_logger(__name__)
lowercase : List[str] = {
"facebook/vit-mae-base": "https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json",
# See all ViT MA... | 423 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModel... | 363 | """simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def _A( lowerCAmelCase ):
def decorator(lowerCAmelCase ):
A__ : Any = getattr(lowerCAmelCase , """handle_key""" , [] )
handle += [key]
... | 363 | 1 |
'''simple docstring'''
def lowerCamelCase_ ( A_ , A_ ):
if not isinstance(A_ , A_ ):
raise ValueError('''iterations must be defined as integers''' )
if not isinstance(A_ , A_ ) or not number >= 1:
raise ValueError(
'''starting num... | 575 |
'''simple docstring'''
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def lowerCamelCase_ ( A_ , A_ ):
__lowerCamelCase = k_size // 2
__lowerCamelCase ... | 575 | 1 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
fr... | 250 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class lowerCAmelCase__ ( __lowerCamelCase ):
"""simple docstring"""
def __init__( self , ... | 250 | 1 |
def A ( snake_case :Any ) -> str:
__UpperCamelCase = 1
__UpperCamelCase = 2
while i * i <= n:
__UpperCamelCase = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
n_divisors *= 2
return n_divisors
... | 710 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase : List[Any] = {
... | 293 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_a : Optional[Any] = logging.get_logger(__name__)
_a : Tuple = {
"""facebook/convnextv2-tiny-1k-224""... | 145 |
"""simple docstring"""
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
_A = logging.getLogger(__name__)
if is_torch_tpu_available(check_device... | 182 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
'google/fnet-large': 'https://huggingface.co/google/fnet-... | 109 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A = {'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PLBartConfi... | 109 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from... | 329 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizer... | 630 | 0 |
"""simple docstring"""
def A( snake_case_ = 50000000 ):
"""simple docstring"""
lowercase__: int = set()
lowercase__: Union[str, Any] = int((limit - 24) ** (1 / 2) )
lowercase__: Optional[int] = set(range(3 ,... | 707 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase = {
"""susnato/ernie-m-base_pytorch""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json""",
"""susnato/ernie-m-l... | 120 | 0 |
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,
StableDiffusionXLImgaImgPipeline,
UNetaD... | 587 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : Optional[int] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
'came... | 587 | 1 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __lowerCamelCase ( __lowerCAmelCase : str ) -> Optional[int]:
def wrapper(*__lowerCAme... | 517 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lic... | 517 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
A = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( ... | 125 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...... | 125 | 1 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAva... | 708 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
A : Optional[int] = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
A : Dict ... | 273 | 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,
AutoM... | 257 |
from typing import Any
import numpy as np
def UpperCamelCase ( _a ) -> bool:
'''simple docstring'''
return np.array_equal(_a , matrix.conjugate().T )
def UpperCamelCase ( _a , _a ) -> Any:
'''simple docstring... | 257 | 1 |
'''simple docstring'''
import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = "▁"
a_ = {"voca... | 92 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
a_ = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two classes) or mu... | 92 | 1 |
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 419 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from transformer... | 419 | 1 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor
... | 703 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torch.uti... | 92 | 0 |
'''simple docstring'''
from collections.abc import Generator
from math import sin
def a ( UpperCamelCase_ : bytes ) -> bytes:
if len(UpperCamelCase_ ) != 32:
raise ValueError('Input must be of length 32' )
snake_case__ =b''
for i in [3, 2, 1, 0]:
little_endian +... | 538 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ : Tuple = {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}
try:
if not is_... | 538 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 630 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 1 |
from collections.abc import Generator
def _SCREAMING_SNAKE_CASE ( ):
'''simple docstring'''
lowerCamelCase_ = 0, 1
while True:
lowerCamelCase_ = b, a + b
yield b
def _SCREAMING_SNAKE_CASE ( lowercase... | 70 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MA... | 47 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase__ : Optional[int] =logging.get_logger(__name__)
UpperCAmelCase__ : Optional[int] ={
''... | 716 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase__ : List[Any] ={'''configuration_yolos''': ['''YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YolosConfig''', '''YolosOnnxConfig''']}
try:
... | 269 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[Any] = logging.get_logger(__name__)
lowerCAmelCase : int = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class _A ( lowerCamelCase__):
SCREAMING_SNAKE_CASE : Union[str, ... | 511 |
'''simple docstring'''
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE_ = {
"n_samples": 6_4,
"horizon": 3_2,
"num_inference_steps": 2_0,
"n_guide_steps": 2, # can set to 0 for faster sampl... | 597 | 0 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _lowercase ( UpperCAmelCase_ , ... | 127 |
import colorsys
from PIL import Image # type: ignore
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : List[Any] = x
snake_case__ : int = y
for step in range(Uppe... | 127 | 1 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transfor... | 575 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if ... | 575 | 1 |
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi.routing import APIRo... | 151 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
UpperCamelCase : Any = logging.get_logger(__name__)
clas... | 151 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
lowerCamelCase :Optional[Any] = logging.get_logger(__nam... | 487 |
def __snake_case ( _UpperCamelCase ) -> list[int]:
if length <= 0 or not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in range(_UpperCamelCase )]
if __name__ == "__main__":
print(hex... | 487 | 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 OptionalDep... | 183 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _UpperCAmelCase ( SCREAMING_SNAKE_CASE_ ):
@staticmethod
@abstractmethod
def a_ ( lowercase_ ) -> Optional[Any]:
raise NotIm... | 183 | 1 |
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_te... | 307 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
_snake_case = logging... | 307 | 1 |
from string import ascii_lowercase, ascii_uppercase
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
if not sentence:
return ""
SCREAMING_SNAKE_CASE : Union[str, Any] = dict(zip(lowercase , lowercase ) )
return lower_to_upper.get(senten... | 711 |
from __future__ import annotations
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[Any] = str(lowercase )
return n == n[::-1]
def lowerCamelCase__ ( lowercase = 1000000 ):
"""simple docstring"""
SC... | 488 | 0 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorTy... | 517 |
'''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
SCREAMING_SNAKE_CASE_ = version.parse(ver... | 517 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case : Dict = '▁'
_snake_case : Tu... | 707 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
Reques... | 214 | 0 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configur... | 106 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCAmelCase__ : List[Any] = 4
UpperCAmelCase__ : Optional[Any] = ... | 313 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
__lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase__( __SCREAMING_SNAKE_CASE ):
def __init__( self ,*__UpperCAme... | 705 | """simple docstring"""
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCame... | 536 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 454 |
import functools
def lowerCAmelCase__ ( _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
__a = len(_SCREAMING_SNAKE_CASE )
__a = len(_SCREAMING_SNAKE_CASE )
@functools.cache
def min_distance(_SCREAMIN... | 225 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmel... | 492 |
"""simple docstring"""
def _snake_case ( lowercase__ ):
_lowerCamelCase : List[str] = abs(lowercase__ )
_lowerCamelCase : Optional[int] = 0
while n > 0:
res += n % 10
n //= 10
return res
def _snake_case (... | 492 | 1 |
"""simple docstring"""
from math import sqrt
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> bool:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
lowercase__: Optional[Any] = True
# 0 an... | 586 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTConfig", "DeiTOnnxConfig... | 586 | 1 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is_vi... | 376 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class a ( __UpperCAmelCase ):
@staticmethod
@abstractmethod
def UpperCAmelCase__ ( snake_case__ : ArgumentParser ):
"""simple docstring"""
raise NotImplementedError(... | 376 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.