code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
class lowercase_ :
def __init__( self , lowercase_ , lowercase_=None , lowercase_=None) -> Tuple:
a__ =data
a__ =previous
a__ =next_node
def __str__( self) -> str:
return F"""{self.data}"""
de... | 20 |
"""simple docstring"""
__magic_name__ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def _A ( __lowercase , __lowercase , __lowercase , __lowercase ... | 129 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase__ )
class __A ( UpperCamelCase__ ):
# `task` is not a ClassVar sin... | 21 |
"""simple docstring"""
def _A ( __lowercase = 10 , __lowercase = 22 ):
"""simple docstring"""
lowerCamelCase__ = range(1 , __lowercase )
lowerCamelCase__ = range(1 , __lowercase )
return sum(
... | 129 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin,... | 22 |
"""simple docstring"""
def _A ( __lowercase = 200_0000 ):
"""simple docstring"""
lowerCamelCase__ = [0 for i in range(n + 1 )]
lowerCamelCase__ = 1
lowerCamelCase__ = 1
for i in range(2 , int(n**0.5 ) ... | 129 | 0 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiff... | 23 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
while second != 0:
lowerCamelCase__ = first & second
first ^= second
lowerCamelCase__ = c << 1
return first
... | 129 | 0 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import D... | 24 |
"""simple docstring"""
from __future__ import annotations
def _A ( __lowercase ):
"""simple docstring"""
if len(__lowercase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
... | 129 | 0 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
a_ = logging.get_logger(__name__)
a_ = {
'post_extract_proj': 'feature_projection.projection',
'encoder.pos_conv.... | 25 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE , unittest.TestCase )... | 129 | 0 |
'''simple docstring'''
from __future__ import annotations
__UpperCamelCase = list[list[int]]
# assigning initial values to the grid
__UpperCamelCase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0,... | 26 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 129 | 0 |
import numpy as np
__A : int = [
["a", "b", "c", "d", "e"],
["f", "g", "h", "i", "k"],
["l", "m", "n", "o", "p"],
["q", "r", "s", "t", "u"],
["v", "w", "x", "y", "z"],
]
class lowerCamelCase:
'''simple docstring'''
def __init... | 27 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 129 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
UpperCamelCase_ = TypeVar("T")
class _a ( Generic[T] ):
'''simple docstring'''
def __init_... | 28 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__magic_name__ = 3
def _A ( __lowercase ):
"""simple docstring"""
print("""Generating primitive root of p""" )
while True:... | 129 | 0 |
"""simple docstring"""
from math import ceil
def lowercase ( lowerCAmelCase__ = 1_001 ):
lowerCamelCase_ = 1
for i in range(1 ,int(ceil(n / 2.0 ) ) ):
lowerCamelCase_ = 2 * i + 1
lowerCamelCase_ = 2 * i
lowerCamelCase_ = total + 4 * odd**2 ... | 29 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _A ( __lowercase , __lowercase=None ):
"""simple docstring"""
lowerCamelCase__ = No... | 129 | 0 |
from collections.abc import Sequence
from queue import Queue
class __a:
"""simple docstring"""
def __init__( self ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE=None ,_SCREAMING_SNAKE_CASE=None ) -> Tuple:
UpperCAmelCase... | 30 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = set()
# edges = list of graph's edges
lowerCamelCase__ = get_edges(__lowercase )
# While there are still elements in edges list, take an ar... | 129 | 0 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
lowerCamelCase__ : List[str] = logging.get_logger(__name__)
... | 31 |
"""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 TensorT... | 129 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DU... | 32 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's eas... | 129 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Any = {
"""configuration_megatron_bert""": ["""MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegatronBertConfig"""],
}
try:
if ... | 33 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 129 | 0 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def __snake_case ( ):
"""simple docstring"""
UpperCamelCase = ArgumentParser(
... | 34 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _A ( __lowercase , __lowercase , __lowercase = None ):
"""simple docstring"""
if version.parse(hfh.__version__... | 129 | 0 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def a ( A__ ) -> List[str]:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : List[Any] = {}
SCREAMING_SNAKE_CASE__ : int = job['''started... | 35 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
__magic_name__ = get_logger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : Tuple , SCREAMING_SNAKE_CASE_ : int=None ... | 129 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : List[str] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolv... | 36 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transfo... | 129 | 0 |
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from ...utils import logging
... | 37 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 129 | 0 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
A_ : Dict = 6378137.0
A_ : Optional[Any] = 6356752.314245
A_ : List[str] = 6378137
def UpperCamelCase__ ( __magic_name__ : float , __magic_name__ : float , __magic... | 38 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=_SCREAMING_SNAKE_CASE ):
snake_case = ["speech"]
def __init__( self : Optional[int] , *SCREAMING_SNAKE_CASE_ : Tuple , **SCREAMING_SNAKE_... | 129 | 0 |
from math import factorial
lowerCAmelCase_ = {str(digit): factorial(digit) for digit in range(10)}
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError('''Parameter number... | 39 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_A... | 129 | 0 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils imp... | 40 |
"""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 .tok... | 129 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ = {'''configuration_vit''': ['''VIT_PRETRAINED_CONFIG_AR... | 41 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 129 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ = {
"configuration_owlvit": [
"OWLVIT_P... | 42 |
"""simple docstring"""
__magic_name__ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def _A ( __lowercase , __lowercase , __lowercase , __lowercase ... | 129 | 0 |
def _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(SCREAMING_SNAKE_CASE , x % y )
def _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
r... | 43 |
"""simple docstring"""
def _A ( __lowercase = 10 , __lowercase = 22 ):
"""simple docstring"""
lowerCamelCase__ = range(1 , __lowercase )
lowerCamelCase__ = range(1 , __lowercase )
return sum(
... | 129 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : str = {'configuration_fnet': ['FNET_PRETRAINED_CONFIG_ARCHIVE... | 44 |
"""simple docstring"""
def _A ( __lowercase = 200_0000 ):
"""simple docstring"""
lowerCamelCase__ = [0 for i in range(n + 1 )]
lowerCamelCase__ = 1
lowerCamelCase__ = 1
for i in range(2 , int(n**0.5 ) ... | 129 | 0 |
def A ( ) -> int:
return 1
def A ( lowercase__ : int ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def A ( lowercase__ : int ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) + two_pence(lowercase__ )
def A ( lowercase__ : int ... | 45 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
while second != 0:
lowerCamelCase__ = first & second
first ^= second
lowerCamelCase__ = c << 1
return first
... | 129 | 0 |
"""simple docstring"""
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,... | 46 |
"""simple docstring"""
from __future__ import annotations
def _A ( __lowercase ):
"""simple docstring"""
if len(__lowercase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
... | 129 | 0 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version... | 47 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE , unittest.TestCase )... | 129 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase__ : str = logging.get_logger(__name__)
UpperCAmelCase__ :... | 48 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 129 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
_lowercase : int = ... | 49 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 129 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logg... | 50 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__magic_name__ = 3
def _A ( __lowercase ):
"""simple docstring"""
print("""Generating primitive root of p""" )
while True:... | 129 | 0 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
a__ : Optional[Any] = TypeVar('KEY')
a__ : List[str] = TypeVar('VAL')
@dataclass(frozen=UpperCAmelCase_ , sl... | 51 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _A ( __lowercase , __lowercase=None ):
"""simple docstring"""
lowerCamelCase__ = No... | 129 | 0 |
"""simple docstring"""
def __A ( a_ :int , a_ :int) -> int:
return int((input_a, input_a).count(0) == 0)
def __A ( ) -> None:
assert and_gate(0 , 0) == 0
assert and_gate(0 , 1) == 0
assert and_gate(1 , 0) == 0
... | 52 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = set()
# edges = list of graph's edges
lowerCamelCase__ = get_edges(__lowercase )
# While there are still elements in edges list, take an ar... | 129 | 0 |
def a_ ( lowerCAmelCase_ : str ):
__lowerCAmelCase = ''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def a_ ( lowerCAmelCase_ : str ):
__lowerCAmelCase = ... | 53 |
"""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 TensorT... | 129 | 0 |
from __future__ import annotations
def a__ ( lowercase__ , lowercase__ ):
'''simple docstring'''
UpperCAmelCase_ , UpperCAmelCase_ =position
UpperCAmelCase_ =[
(y + 1, x + 2),
(y - 1, x + 2),
(... | 54 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's eas... | 129 | 0 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE :Dict = logging.get_logger(__name__)
# TODO Update this
SCREAMING_SNAKE_CASE :Dict = {
'facebook/esm-1b':... | 55 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 129 | 0 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _a (lowercase__ : List[Any] , lowercase__ : List[str... | 56 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _A ( __lowercase , __lowercase , __lowercase = None ):
"""simple docstring"""
if version.parse(hfh.__version__... | 129 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ... | 57 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
__magic_name__ = get_logger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : Tuple , SCREAMING_SNAKE_CASE_ : int=None ... | 129 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vis... | 58 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transfo... | 129 | 0 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> ... | 59 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 129 | 0 |
def lowerCamelCase_ ( _UpperCamelCase ) -> str:
"""simple docstring"""
snake_case_ : str = ''''''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def lowerCamelCase_... | 60 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=_SCREAMING_SNAKE_CASE ):
snake_case = ["speech"]
def __init__( self : Optional[int] , *SCREAMING_SNAKE_CASE_ : Tuple , **SCREAMING_SNAKE_... | 129 | 0 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class __lowerCamelCase :
"""simple docstring"""
def __init__( self : List[str] , SCREAMING_SNAKE_CASE__ : List[Any]=2 , SCRE... | 61 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_A... | 129 | 0 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transform... | 62 |
"""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 .tok... | 129 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class a ( lowercase__ ):
... | 63 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 129 | 0 |
def A__ ( snake_case_ : list , snake_case_ : int = 0 ):
SCREAMING_SNAKE_CASE__: Union[str, Any]= length or len(snake_case_ )
SCREAMING_SNAKE_CASE__: Tuple= False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_C... | 64 |
"""simple docstring"""
__magic_name__ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def _A ( __lowercase , __lowercase , __lowercase , __lowercase ... | 129 | 0 |
"""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=__lowerCamelCase )
class __lowercase ( __lowerCamelCase ... | 65 |
"""simple docstring"""
def _A ( __lowercase = 10 , __lowercase = 22 ):
"""simple docstring"""
lowerCamelCase__ = range(1 , __lowercase )
lowerCamelCase__ = range(1 , __lowercase )
return sum(
... | 129 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mob... | 66 |
"""simple docstring"""
def _A ( __lowercase = 200_0000 ):
"""simple docstring"""
lowerCamelCase__ = [0 for i in range(n + 1 )]
lowerCamelCase__ = 1
lowerCamelCase__ = 1
for i in range(2 , int(n**0.5 ) ... | 129 | 0 |
import numpy as np
class A_ :
"""simple docstring"""
def __init__( self : int ) -> int:
_lowercase = (0, 0)
_lowercase = None
_lowercase = 0
_lowercase ... | 67 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
while second != 0:
lowerCamelCase__ = first & second
first ^= second
lowerCamelCase__ = c << 1
return first
... | 129 | 0 |
from __future__ import annotations
def lowercase__ ( A_: int ) -> bool:
"""simple docstring"""
__UpperCAmelCase =str(A_ )
return len(A_ ) == 9 and set(A_ ) == set("""123456789""" )
def lowercase__ ( ) -> int | None:
... | 68 |
"""simple docstring"""
from __future__ import annotations
def _A ( __lowercase ):
"""simple docstring"""
if len(__lowercase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
... | 129 | 0 |
'''simple docstring'''
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dic... | 69 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE , unittest.TestCase )... | 129 | 0 |
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class A( datasets.BuilderConfig ):
'''simple docstring'''
UpperCamelCase = ... | 70 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 129 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
"""microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.j... | 71 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 129 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class __magic_name__ ( __SCREAMING_SNAKE_CASE ):
UpperCamelCase__ = 'SpeechT5FeatureExtractor'
UpperCamelCase__ = 'SpeechT5Tokenizer'
def __init__( self , snake_case_ , snake_case_ ):
super(... | 72 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__magic_name__ = 3
def _A ( __lowercase ):
"""simple docstring"""
print("""Generating primitive root of p""" )
while True:... | 129 | 0 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def lowerCamelCase__ ... | 73 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _A ( __lowercase , __lowercase=None ):
"""simple docstring"""
lowerCamelCase__ = No... | 129 | 0 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testi... | 74 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = set()
# edges = list of graph's edges
lowerCamelCase__ = get_edges(__lowercase )
# While there are still elements in edges list, take an ar... | 129 | 0 |
'''simple docstring'''
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
UpperCamelCase__ = {
'''E''': 12.70,
'''T''': 9.06,
'''A''': 8.17,
'''O''': 7.51,
'''I''': 6.97,
'''N''': 6.75,
'''S''': 6.33,
'''H''': 6.09,
'''R''... | 75 |
"""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 TensorT... | 129 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d-tiny-100k/resolve/... | 76 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's eas... | 129 | 0 |
"""simple docstring"""
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... | 77 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 129 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer, TF... | 78 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _A ( __lowercase , __lowercase , __lowercase = None ):
"""simple docstring"""
if version.parse(hfh.__version__... | 129 | 0 |
import math
import qiskit
def _lowerCamelCase ( __lowerCamelCase = 1 , __lowerCamelCase = 1 , __lowerCamelCase = 1 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
if (
isinstance(__lowerCamelCase , __lowerCamelCase )... | 79 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
__magic_name__ = get_logger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : Tuple , SCREAMING_SNAKE_CASE_ : int=None ... | 129 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 80 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transfo... | 129 | 0 |
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
DPR_CONTEXT_ENCOD... | 81 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 129 | 0 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowercase_... | 82 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=_SCREAMING_SNAKE_CASE ):
snake_case = ["speech"]
def __init__( self : Optional[int] , *SCREAMING_SNAKE_CASE_ : Tuple , **SCREAMING_SNAKE_... | 129 | 0 |
"""simple docstring"""
def snake_case_ ( A_ : int, A_ : list ):
'''simple docstring'''
_enforce_args(A_, A_ )
if n == 0:
return 0
_lowerCamelCase : Tuple = float('''-inf''' )
for i in range(1, ... | 83 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_A... | 129 | 0 |
from __future__ import annotations
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
lowercase = str(__SCREAMING_SNAKE_CASE )
return n == n[::-1]
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE = 100_0000 ):
lowercase = 0
for i in range(1 , __SCRE... | 84 |
"""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 .tok... | 129 | 0 |
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,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
Stable... | 85 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 129 | 0 |
from typing import List
from .keymap import KEYMAP, get_character
def __snake_case ( __UpperCamelCase : str ):
"""simple docstring"""
def decorator(__UpperCamelCase : Union[str, Any] ):
A_ = getattr(__UpperCamelCase ,"handle_key" ,[] )
... | 86 |
"""simple docstring"""
__magic_name__ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def _A ( __lowercase , __lowercase , __lowercase , __lowercase ... | 129 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase : Any = logging.get_logger(__name__)
_lowerCamelCase : str = {
"""andreasmadsen/ef... | 87 |
"""simple docstring"""
def _A ( __lowercase = 10 , __lowercase = 22 ):
"""simple docstring"""
lowerCamelCase__ = range(1 , __lowercase )
lowerCamelCase__ = range(1 , __lowercase )
return sum(
... | 129 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""... | 88 |
"""simple docstring"""
def _A ( __lowercase = 200_0000 ):
"""simple docstring"""
lowerCamelCase__ = [0 for i in range(n + 1 )]
lowerCamelCase__ = 1
lowerCamelCase__ = 1
for i in range(2 , int(n**0.5 ) ... | 129 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attentio... | 89 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
while second != 0:
lowerCamelCase__ = first & second
first ^= second
lowerCamelCase__ = c << 1
return first
... | 129 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google... | 90 |
"""simple docstring"""
from __future__ import annotations
def _A ( __lowercase ):
"""simple docstring"""
if len(__lowercase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
... | 129 | 0 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_... | 91 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE , unittest.TestCase )... | 129 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( ... | 92 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 129 | 0 |
"""simple docstring"""
import re
def __A (_SCREAMING_SNAKE_CASE ) ->bool:
"""simple docstring"""
lowerCAmelCase__ :str = re.compile(r'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' )
if match := re.search(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
return mat... | 93 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 129 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
fro... | 94 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__magic_name__ = 3
def _A ( __lowercase ):
"""simple docstring"""
print("""Generating primitive root of p""" )
while True:... | 129 | 0 |
"""simple docstring"""
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSample... | 95 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _A ( __lowercase , __lowercase=None ):
"""simple docstring"""
lowerCamelCase__ = No... | 129 | 0 |
"""simple docstring"""
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __A ( unittest.TestCase ):
def lowerCamelCase__ ( self : Dict ) -> None... | 96 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = set()
# edges = list of graph's edges
lowerCamelCase__ = get_edges(__lowercase )
# While there are still elements in edges list, take an ar... | 129 | 0 |
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
__a = 'src/transformers'
# This is to make sure the transformers module imported is the one i... | 97 |
"""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 TensorT... | 129 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 98 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's eas... | 129 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, rand... | 99 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 129 | 0 |
def __snake_case ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) -> int:
SCREAMING_SNAKE_CASE__ = set(range(3 , lowerCAmelCase_ , 2 ) )
primes.add(2 )
for p in range(3 , lowerCAmelCase_ , 2 ):
if p not in primes:
continue
prim... | 100 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _A ( __lowercase , __lowercase , __lowercase = None ):
"""simple docstring"""
if version.parse(hfh.__version__... | 129 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Any ={
'configuration_time_series_transformer': [
'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TimeSeriesTransformerCon... | 101 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
__magic_name__ = get_logger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : Tuple , SCREAMING_SNAKE_CASE_ : int=None ... | 129 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
... | 102 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transfo... | 129 | 0 |
"""simple docstring"""
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import Gr... | 103 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 129 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCamelCase = {"""processing_wav2vec2_with_lm""": ["""Wav2Vec2ProcessorWithLM"""]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
i... | 104 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=_SCREAMING_SNAKE_CASE ):
snake_case = ["speech"]
def __init__( self : Optional[int] , *SCREAMING_SNAKE_CASE_ : Tuple , **SCREAMING_SNAKE_... | 129 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ : str = logging.get_logger(__name__)
UpperCamelCase__ : str = {
'''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json... | 105 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_A... | 129 | 0 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def lowerCamelCase_ ( lowerCAmelCase__ : NDArray[floataa] , lowerCAmelCase__ : NDArray[floataa] , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : int , ) -> list[float]... | 106 |
"""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 .tok... | 129 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( __snake_case : List[Any] ):
_A = len(__snake_case )
for i in range(length - 1 ):
_A = i
for k in range(i + 1 , __snake_case ):
if collection[k] < collection[least]:
... | 107 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 129 | 0 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__a: Optional[int] = logging.get_logger('''transformers.models.speecht5''')
def _SCREAMING_SNAKE_CASE ( __snake_case , __... | 108 |
"""simple docstring"""
__magic_name__ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def _A ( __lowercase , __lowercase , __lowercase , __lowercase ... | 129 | 0 |
'''simple docstring'''
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECK... | 109 |
"""simple docstring"""
def _A ( __lowercase = 10 , __lowercase = 22 ):
"""simple docstring"""
lowerCamelCase__ = range(1 , __lowercase )
lowerCamelCase__ = range(1 , __lowercase )
return sum(
... | 129 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( lowerCamelCase_ : Optional[Any] , lowerCamelCase_ : int ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 502 |
"""simple docstring"""
def _A ( __lowercase = 200_0000 ):
"""simple docstring"""
lowerCamelCase__ = [0 for i in range(n + 1 )]
lowerCamelCase__ = 1
lowerCamelCase__ = 1
for i in range(2 , int(n**0.5 ) ... | 129 | 0 |
a__: Tuple = 256
# Modulus to hash a string
a__: Dict = 1_000_003
def UpperCamelCase__( UpperCamelCase__ : str , UpperCamelCase__ : List[str] )->Optional[Any]:
A__ = len(__lowercase )
A__ = len(__lowercase )
... | 190 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
while second != 0:
lowerCamelCase__ = first & second
first ^= second
lowerCamelCase__ = c << 1
return first
... | 129 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IM... | 484 |
"""simple docstring"""
from __future__ import annotations
def _A ( __lowercase ):
"""simple docstring"""
if len(__lowercase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
... | 129 | 0 |
"""simple docstring"""
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
Distil... | 595 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE , unittest.TestCase )... | 129 | 0 |
import torch
from accelerate import PartialState
from accelerate.utils.operations import broadcast, gather, gather_object, pad_across_processes, reduce
def _UpperCAmelCase ( a : Any ):
return (torch.arange(state.num_processes ) + 1.0 + (state.num_processes * state.process_index)).to(sta... | 654 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 129 | 0 |
import heapq
import sys
import numpy as np
_lowercase : Optional[Any] =tuple[int, int]
class snake_case__ :
"""simple docstring"""
def __init__( self ) -> str:
"""simple docstring"""
a__ : Any = []
... | 136 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 129 | 0 |
"""simple docstring"""
import warnings
warnings.warn(
"""memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: """
"""`from accelerate import find_executable_batch_size` to avoid this warning.""",
FutureWarning,
)
| 341 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__magic_name__ = 3
def _A ( __lowercase ):
"""simple docstring"""
print("""Generating primitive root of p""" )
while True:... | 129 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transfo... | 42 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _A ( __lowercase , __lowercase=None ):
"""simple docstring"""
lowerCamelCase__ = No... | 129 | 0 |
import torch
def _A ( ):
"""simple docstring"""
if torch.cuda.is_available():
a__ : List[Any] =torch.cuda.device_count()
else:
a__ : Any =0
print(f'''Successfully ran on {num_gpus} GPUs''' )
if __name__ == "__main__":
main()
... | 563 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = set()
# edges = list of graph's edges
lowerCamelCase__ = get_edges(__lowercase )
# While there are still elements in edges list, take an ar... | 129 | 0 |
"""simple docstring"""
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def lowerCamelCase_ ... | 506 |
"""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 TensorT... | 129 | 0 |
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