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 |
|---|---|---|---|---|
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")
class lowercase_... | 0 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __A ( UpperCa... | 1 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
'''simple docstring'''
class __lowerCAmelCase : # Public class to implement a graph
'''simple docstring'''
def __init__(self : int , UpperCamelCase : int , UpperCamelCase : int , UpperCamelCase : list[list[bool]] ):
'''simple ... | 2 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils... | 3 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
'''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=l... | 4 | """simple docstring"""
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():
from PIL import Image
... | 77 | 0 |
import qiskit
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> qiskit.result.counts.Counts:
"""simple docstring"""
_lowercase =qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
_lowercase ... | 5 | """simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingSt... | 77 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimen... | 6 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common... | 7 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase_ = {
'''configuration_convnext''': ['''CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ConvNextC... | 8 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 0 |
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
__lowerCAmelCase : Optional[int] ='\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Mode... | 9 | """simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 77 | 0 |
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 torch
if is_tf_availabl... | 10 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
def _UpperCAmelCase (UpperCamelCase__ : int ):
_A : Tuple = len(UpperCamelCase__ )
_A : List[str] = sum(UpperCamelCase__ )
_A : Tuple = [[False for x in range(s + 1 )] for y in range(n + 1 )]
f... | 11 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
import numpy as np
def lowerCamelCase__ ( A__ : np.ndarray , A__ : float ):
'''simple docstring'''
return np.where(vector > 0 , A__ , (alpha * (np.exp(A__ ) - 1)) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 12 | """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_VARS... | 77 | 0 |
import math
lowerCAmelCase : Dict = 10
lowerCAmelCase : Dict = 7
lowerCAmelCase : Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def A_ ( _UpperCAmelCase = 20 ):
SCREAMING_SNAKE_CASE_: Union[str, Any] = math.comb(_UpperCAmelCase , ... | 13 | """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, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... | 14 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
SCREAMING_SNAKE_CASE :Optional[Any] = Mapping[str, np.ndarray]
SCREAMING_SNAKE_CASE :List[str] = Mapping[str... | 15 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
"""simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import Ba... | 16 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
'facebook/nllb-moe-54B': 'https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json',
}
class _lowerCAmelCase ( low... | 17 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class a__ ( unittest.TestCase ):
A = inspect.getfile(accelerate.test_... | 18 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface impo... | 19 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
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.transforms.functional impo... | 20 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 0 |
def UpperCamelCase_( lowerCamelCase_ ) -> list[int]:
if num <= 0:
raise ValueError('Input must be a positive integer' )
_lowercase : str = [True] * (num + 1)
_lowercase : str = 2
while p * p <= num:
if primes[p]:
... | 21 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
'''simple docstring'''
def UpperCAmelCase_ ( __lowercase : int , __lowercase : Optional[int] ) -> str:
'''simple docstring'''
_UpperCAmelCase = 0
_UpperCAmelCase = len(__lowercase ) - 1
while left <= ... | 22 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 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:
f... | 23 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
snake_case_ = logging.get_logg... | 24 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase__ : str = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-j... | 25 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase ( UpperCamelCase__,UpperCamelCase__ ):
@register_to_config
def __init__( self , *,
_a = 4 , _a = 768 , _a ... | 26 | """simple docstring"""
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():
from PIL import Image
... | 77 | 0 |
'''simple docstring'''
import math
def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ):
__a : int = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(_SCREAMING_SNAKE_CASE )
def lowerCamelCase (_SCREAMING_SNAKE_... | 27 | """simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingSt... | 77 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __lowerCamelCase ( A__ , A__ ) -> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b , 2 ) for ... | 28 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
def lowercase__ ( __snake_case : int ):
'''simple docstring'''
UpperCAmelCase_ : list[list[int]] = [[0 for _ in range(__snake_case )] for _ in range(m + 1 )]
for i in range(m + 1 ):
UpperCAmelCase_ : Optional[A... | 29 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
def a ( snake_case__: int , snake_case__: int ):
'''simple docstring'''
return base * power(snake_case__ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('Raise base to the power of exponent using recursion...')
__a ... | 30 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 0 |
'''simple docstring'''
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase_ (snake_case__ ):
'''simple docstring'''
__UpperCamelCase: Optional[Any] = (UnCLIPScheduler,)
def _A ( self : Li... | 31 | """simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 77 | 0 |
def SCREAMING_SNAKE_CASE_ ( __A : list[list] ) -> list[list]:
"""simple docstring"""
a_ : List[str] = current_set.copy()
for row_index, row in enumerate(__A ):
a_ : List[str] = row[0]
for column_index, column ... | 32 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
__A : Any = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full RobertaForMas... | 33 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class _a ( __a ):
__a : Dict = Distil... | 34 | """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_VARS... | 77 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __snake_case( _lowerCAmelCase , _lowerCAmelCase ) -> float:
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(_lowerCAmelCase , _lowerCAmelCas... | 35 | """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, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import logging
... | 36 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acce... | 37 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
print((lambda quine: quine % quine)('''print((lambda quine: quine %% quine)(%r))'''))
| 38 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.traini... | 39 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
__lowercase = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Tran... | 40 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
'''simple docstring'''
_A : List[str] =8.314_4598
def SCREAMING_SNAKE_CASE_ (UpperCamelCase , UpperCamelCase ) -> float:
if temperature < 0:
raise Exception("""Temperature cannot be less than 0 K""" )
if mo... | 41 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : int = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/... | 42 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 0 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if number > 0:
raise ValueError('''input must be a negative integer''' )
__UpperCamelCase :str = len(bin(SCREAMING_SNAKE_CASE )[3:] )
__UpperCamelCase :Optional[Any] = bin(abs(SCREAMING_SNAKE_CASE ) -... | 43 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_ava... | 44 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
"""simple docstring"""
# 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/... | 45 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class lowercase ( _UpperCAmelCase ):
def _snake_case ( self ) -> str:
return [
{"col_1": 3, "col_2": "a"... | 46 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
'''simple docstring'''
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_... | 47 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils impor... | 48 | """simple docstring"""
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():
from PIL import Image
... | 77 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__snake_case :Union[str, Any] = logging.get_logger(__name__)
__snake_case :Optional[int] = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network... | 49 | """simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingSt... | 77 | 0 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
_UpperCAmelCase : List[Any] = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase ) -> int:
... | 50 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
... | 51 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase : Union[str, Any] = {
"""configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
"""tokenization_tapas"... | 52 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 0 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelD... | 53 | """simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 77 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMSche... | 54 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def __snake_case ( ):
raise RuntimeError("CUDA out of memory." )
class... | 55 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
'''simple docstring'''
import math
from collections.abc import Iterator
from itertools import takewhile
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or... | 56 | """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_VARS... | 77 | 0 |
"""simple docstring"""
from ... import PretrainedConfig
A : List[Any] = {
"sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : ... | 57 | """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, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ =... | 58 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("""/""", """."""),
("""layer_""", """layers."""),
("""... | 59 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _snake_case ( _snake_case : np.ndarray , _snake_case : np.ndarray ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(_snake_case , _snak... | 60 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
_a = 'examples/'
_a = {
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$'... | 61 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
_A ... | 62 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase_ : Tuple = {
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'toke... | 63 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils imp... | 64 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface ... | 65 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__a = logging.get_logger("transformers.models.speecht5")
def A_ ( _lowercase, _lowercase, _lowercase ):
... | 66 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
'''simple docstring'''
def __lowerCAmelCase ( UpperCamelCase__ = 10 , UpperCamelCase__ = 10_00 , UpperCamelCase__ = True ) -> int:
assert (
isinstance(UpperCamelCase__ , UpperCamelCase__ )
and isinstance(UpperCamelCase__ , UpperCamelCase__ )
and isinstan... | 67 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
import os
import numpy
import onnx
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: int ) -> Optional[int]:
'''simple docstring'''
A__ = a.name
A__ = b.name
A__ = ""
A__ = ""
A__ = a == b
... | 68 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
"""simple docstring"""
import sys
from collections import defaultdict
class UpperCamelCase :
def __init__( self) -> Optional[int]:
snake_case_ = []
def a_ ( self, lowerCAmelCase__) -> Any:
return self.node_pos... | 69 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xope... | 70 | """simple docstring"""
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():
from PIL import Image
... | 77 | 0 |
def A ( a_ ,a_ ) -> int:
return 1 if input_a == input_a else 0
def A ( ) -> None:
assert xnor_gate(0 ,0 ) == 1
assert xnor_gate(0 ,1 ) == 0
assert xnor_gate(1 ,0 ) == 0
as... | 71 | """simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingSt... | 77 | 0 |
"""simple docstring"""
import numpy as np
def snake_case_ ( A_ : np.ndarray, A_ : float ):
'''simple docstring'''
return np.where(vector > 0, A_, (alpha * (np.exp(A_ ) - 1)) )
if __name__ == "__main__":
import doctest
doctest.t... | 72 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAG... | 73 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
"""simple docstring"""
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 100 * 2**20, 900 * 2**20] )
def ... | 74 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 0 |
'''simple docstring'''
a_ : Dict = 8.3_14_45_98
def a_ ( __snake_case : float , __snake_case : float ) -> float:
"""simple docstring"""
if temperature < 0:
raise Exception('''Temperature cannot be l... | 75 | """simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'configuration_distilbert': [
'DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 76 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, 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
fr... | 78 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'... | 79 | """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_VARS... | 77 | 0 |
'''simple docstring'''
from math import pi, sqrt
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
if num <= 0:
raise ValueError("math domain error" )
if num > 171.5:
raise OverflowError("math range error" )
elif ... | 80 | """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, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils impor... | 77 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __A ( metaclass=_SCREAMING_SNAKE_CASE ):
"""simple docstring"""
__lowerCAmelCase = ["onnx"]
def __init__( self , *__A , **__A ) -> Di... | 81 | """simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 | 0 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowerCamelCase__ ) , ... | 82 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
snake_case_ : int = {'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP',... | 83 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 0 |
"""simple docstring"""
def _snake_case ( lowercase__ : dict ) -> set:
'''simple docstring'''
lowerCAmelCase_ :Any = set()
# edges = list of graph's edges
lowerCAmelCase_ :List[Any] = get_edges(lowercase__ )
# While there are st... | 84 | """simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 77 | 0 |
'''simple docstring'''
def UpperCamelCase_( snake_case : int ):
'''simple docstring'''
if not isinstance(snake_case , snake_case ):
raise TypeError("only integers accepted as input" )
else:
snake_case_ = st... | 85 | """simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def a_ ( _lowerCAmelCase : jnp.ndarray , _lowerCAmelCase : int , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1 , _lowerCAmelCase : float = 1.0E4 , _lowerCAmelCase : bool = False , _lo... | 77 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase__ = {
"""configuration_longformer""": [
"""LONGFORMER_PRETRAINED_C... | 86 | """simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( _lowerCAmelCase : Callable[[int | float], int | float] , _lowerCAmelCase : int | float , _lowerCAmelCase : int | float , _lowerCAmelCase : int = 100 , ):
''... | 77 | 0 |
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 import PatchingSpec
from ..... | 87 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Tuple = {
"configuration_whisper": ["WHISPER... | 77 | 0 |
import re
import string
import numpy as np
import datasets
__lowerCAmelCase : Optional[int] = '\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'
__lowerCAmelCase : Optional... | 88 | """simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( _lowerCAmelCase : str ):
'''simple docstring'''
lowercase__ : int = args.pruning_method
... | 77 | 0 |
'''simple docstring'''
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def __lowerCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> tuple[int | None, int |... | 89 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : int ) -> list:
"""simple docstring"""
__lowerCamelCase = int(UpperCamelCase__ )
if n_element < 1:
__lowerCamelCase = ValueError('a should be a positive number' )
... | 90 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self , a , a , a , a , a , a=0.2 , a=0.2 ) -> Dict:
lowercase__ : Any = bp_numa
lowercase__ ... | 77 | 0 |
"""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_availabl... | 91 | """simple docstring"""
from collections.abc import Generator
def a_ ( ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = 0, 1
while True:
lowercase__ , lowercase__ : Optional[int] = b, a + b
yi... | 77 | 0 |
from __future__ import annotations
from collections.abc import Callable
def _a ( SCREAMING_SNAKE_CASE_ : Callable[[int | float], int | float] , SCREAMING_SNAKE_CASE_ : int | float , SCREAMING_SNAKE_CASE_ : int | float , SCREAMING_SNAKE_CAS... | 92 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 0 |
'''simple docstring'''
def snake_case_ ( __SCREAMING_SNAKE_CASE : int = 1000 ):
"""simple docstring"""
lowercase_ : Optional[int] = 2**power
lowercase_ : Any = str(__SCREAMING_SNAKE_CASE )
l... | 93 | """simple docstring"""
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():
from PIL import Image
... | 77 | 0 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
snake_case : str = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'... | 94 | """simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingSt... | 77 | 0 |
from string import ascii_uppercase
UpperCAmelCase : int = {char: i for i, char in enumerate(ascii_uppercase)}
UpperCAmelCase : Optional[Any] = dict(enumerate(ascii_uppercase))
def _A ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : str ... | 95 | """simple docstring"""
_UpperCamelCase : Union[str, Any] = 8.3_1_4_4_5_9_8
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
... | 77 | 0 |
"""simple docstring"""
from math import factorial, pi
def _snake_case ( lowercase__ , lowercase__ = 30 ):
if not isinstance(lowercase__ , (int, float) ):
raise ValueError('maclaurin_sin() requires either an int or float for theta' )
... | 96 | """simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
# `task` is not a ClassVar since we want it to be part ... | 77 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase ( A__ ):
"""simple docstring"""
_a = (DDPMScheduler,)
def lowerCAmelCase__ ( self , **UpperCamelCase_ ):
'''simple docs... | 97 | """simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_UpperCamelCase : Any = re.compile(r"\b(a|an|the)\b", re.UNICODE)
_UpperCamelCase : Union[str, Any] = None
def a_ ( ):
... | 77 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate... | 98 | """simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 77 | 0 |
import random
class A__ :
"""simple docstring"""
@staticmethod
def __lowercase ( lowercase) -> tuple[list[int], list[int]]:
'''simple docstring'''
a__ : Union[str, Any] = [ord(lowercase) for i in text]
a__ : int = []... | 99 | """simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 77 | 0 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
__magic_name__ = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3... | 100 | """simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a)
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : str = field(default="language-modeling" , metad... | 77 | 0 |
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