code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torch
i... | 68 |
from __future__ import annotations
def snake_case_ ( snake_case , snake_case ) -> list[int]:
lowercase__: List[str] = 0
lowercase__: Dict = len(snake_case ) - 1
while i < j:
if nums[i] + nums[j] == target:
... | 196 | 0 |
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def _a ( UpperCAmelCase ) -> Tuple:
... | 265 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
_A : Optional[int] = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
... | 265 | 1 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class __snake_case ( unittest.TestCase ):
@re... | 290 | """simple docstring"""
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
lowercase__ = logging.getLogger(__name__)
class __snake_case :
def __init__( self) -> ... | 290 | 1 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test... | 359 |
from math import ceil
def lowerCamelCase_ ( lowerCAmelCase: Tuple , lowerCAmelCase: Union[str, Any] )-> str:
_snake_case : Union[str, Any] = list(range(0 , lowerCAmelCase ) )
_snake_case : int = [item for sublist in list(device... | 260 | 0 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'vocab_file': 'vocab.json',
'tokenizer_config_file': 'tokenizer_confi... | 11 |
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_table,
)
fro... | 11 | 1 |
"""simple docstring"""
def a__ ( ) -> int:
lowerCamelCase = 0
for i in range(1 , 10_01 ):
total += i**i
return str(snake_case__ )[-10:]
if __name__ == "__main__":
print(solution())
| 168 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCAmelCase : List[Any] ... | 168 | 1 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class __lowerCamelCase :
"""simple docstring"""
UpperCamelCase__ = None
def UpperCamelCase ( self ):
"""simpl... | 39 |
def __UpperCAmelCase ( __a : int ,__a : list[int] ,__a : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(__a : int ) -> int:
if target < 0:
return 0
if target == 0:
return 1
... | 235 | 0 |
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 .tokenization_big_bird import ... | 78 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 78 | 1 |
from __future__ import annotations
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self , __lowercase) -> None:
__UpperCamelCase :Optional[int] = data
__UpperCamelCase :Node | None = None
__UpperCamelCase :Node | None = Non... | 43 |
"""simple docstring"""
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization... | 144 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _lowerCAmelCase :
def __init__( self , UpperCamelCase__ ) -> Optional[Any]:
'''simple docstring'''
snake_case : list[dict] = []
self.adlist... | 112 |
"""simple docstring"""
def __lowerCAmelCase ( lowercase : int , lowercase : int , lowercase : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowercase : int , lowercase : int ) -> int:
# BASE... | 112 | 1 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __lowerCAmelCase ( lowerCAmelCase__ ):
def __init__( self , __UpperCAmelCase , ... | 330 |
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_torch... | 330 | 1 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
SCREAMING_SNAKE_CASE__:List[str] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_copies # noqa:... | 268 | """simple docstring"""
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__:Tu... | 268 | 1 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __magic_name__ ( ):
SCREAMING_SNAKE_CASE_: int =[randint(-1000 , 1000 ) for i in range(10 )]
SCREAMIN... | 173 |
def lowerCamelCase__ ( a ) -> bool:
_A: Dict = [int(a ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(a ) == 4 and all(0 <= int(a ) <= 2_54 for octet in octets )
if __name__ == "__main__":
UpperCAmelCase__ : str = ... | 121 | 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... | 350 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def a_ ( _lowercase ):
# This defines a "chinese character" as anything in the CJK Unicode bl... | 128 | 0 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json""",
... | 259 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 259 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
... | 331 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.n... | 331 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=_a )
class UpperCAmelCase_ ( _a ):
"""simple docstring"""
UpperCAmelCase__ ... | 235 |
'''simple docstring'''
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
A_ = re.compile(R"^(?P<major>\d+)" R"\.(?P<minor>\d+)" R"\.(?P<patch>\d+)$")
@total_ordering
@dataclass... | 139 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
a__ : List[str] = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 358 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
a__ : Optional[int] = '%20'.join(argv[1:]) if len(argv) > 1 ... | 243 | 0 |
import copy
import re
class __SCREAMING_SNAKE_CASE :
A : str = 'hp'
A : int = {}
A : List[Any] = None
@classmethod
def __lowerCamelCase ( cls , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ... | 337 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self , SCREAMING_SNAKE_CASE__=0 ): # a graph with Node 0,1,...,N-1
lowercase : List[Any] = n
lowercase : List[Any] = [
[math.inf for j in rang... | 337 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowercase : Optional[Any] = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config"... | 363 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowerCAmelCase... | 264 | 0 |
"""simple docstring"""
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
lowe... | 81 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase_ : Optional[Any] = {}
try:
... | 81 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ : int = logging.get_logger(__name__)
UpperCamelCase_ : Tuple = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-ba... | 142 |
'''simple docstring'''
from manim import *
class _a ( __lowerCAmelCase ):
def _lowercase ( self ) -> Optional[int]:
_snake_case = Rectangle(height=0.5 ,width=0.5 )
_snake_case = Rectangle(height=0.4_6 ,width=0.4_6 ... | 142 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__Upp... | 84 |
"""simple docstring"""
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
d... | 84 | 1 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 352 |
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available()... | 196 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils impor... | 86 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 86 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowerCamelCase ( metaclass=A_ ):
'''simple docstring'''
A_ : Optional[Any] = ["torch", "transformers", "onnx"]
def __init__( self : Optional[int] , *_A : Optional[int... | 360 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _lowerCamelCase ( unittest.TestC... | 275 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
__A = logging.get_logger(__name__)
__A = ... | 10 |
class _SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__(self : Optional[Any] , UpperCAmelCase_ : int) ->Optional[int]:
'''simple docstring'''
lowerCamelCase__: Any =n
lowerCamelCase__: Tuple =[None] * self.n
lowerCamelCase__: ... | 10 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 279 |
def lowerCamelCase_ ( _UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError('''multiplicative_persistence() only accepts integral values''' )
if num < 0:
raise ValueError('''multipl... | 279 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a_ : Optional[Any] = logging.get_logger(__name__)
a_ : List[str] = {
"""sh... | 55 |
"""simple docstring"""
from typing import Any
class a :
def __init__( self : Tuple , __SCREAMING_SNAKE_CASE : Any ) -> List[Any]:
lowerCamelCase_ = data
lowerCamelCase_ = ... | 183 | 0 |
'''simple docstring'''
#
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc_per_node 2 --nno... | 135 |
'''simple docstring'''
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... | 135 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( snake_case__ , snake_case__ ,... | 3 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class UpperCAmelCase :
def __init__( self : str , __snake_case : Any ) -> str:
_lowerCAmelCase = str(id_ )
_lo... | 70 | 0 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''google/efficient... | 356 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
raise OptionalDepende... | 78 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase_ = {'''configuration_swin''': ['''SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SwinConfig''', '''SwinOnnxConfig''']}
try:
if not is_torch_avail... | 8 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def __lowerCamelCase ( a_ : str , a_ : Dict , a_ : Any , a_ : str ) -> str:
__SCREAMING_SNAKE_CASE :... | 191 | 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_accelera... | 202 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 202 | 1 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class __lowerCAmelCase :
"""simple docstring"""
def __ini... | 90 |
from __future__ import annotations
import unittest
from transformers import 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, random_attention_mask
from ... | 170 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __magic_name__ ( __UpperCAmelCase , un... | 371 |
"""simple docstring"""
def lowerCamelCase (a_ :list , a_ :list , a_ :int , a_ :int , a_ :int) -> int:
if index == number_of_items:
return 0
lowercase :Optional[int] = 0
lowercase :str = 0
lowercase ... | 172 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import... | 269 |
"""simple docstring"""
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
__snake_case : Optional[int] = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluati... | 269 | 1 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class SCREA... | 251 |
'''simple docstring'''
from __future__ import annotations
import time
import numpy as np
lowerCAmelCase : List[Any] = [8, 5, 9, 7]
lowerCAmelCase : str = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
lowerCAmelCase : Tuple = ... | 251 | 1 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 340 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/config.json''',
'''xlnet-large-cased''': '''https://huggingface.co/... | 340 | 1 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE_ ( __A : int = 4 ) -> list[list[int]]:
_SCREAMING_SNAKE_CASE = abs(a__ ) or 4
return [[1 + x + y * row_size for x in range(a__ )] for y in range(a__ )]
def SCREAMING_SNAKE_CASE_ ( __A ... | 360 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ =... | 111 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
snake_case__ : int ... | 60 |
"""simple docstring"""
import numpy as np
def _snake_case ( _snake_case : np.array ):
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 60 | 1 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class _SCREAMING_SNAKE_CASE ( A__ ):
UpperCAmelCase_ :List[str] = (UnCLIPScheduler,)
def __lowerCAmelCase ( self ... | 1 |
"""simple docstring"""
from __future__ import annotations
__UpperCAmelCase = 1.6021e-19 # units = C
def _snake_case ( lowercase__ : float , lowercase__ : float , lowercase__ : float , ) -> tuple[str, float]:
'''simple docstring'''
... | 1 | 1 |
def SCREAMING_SNAKE_CASE_ ( __A : list ) -> list:
"""simple docstring"""
if len(__A ) <= 1:
return lst
a_ : List[Any] = 1
while i < len(__A ):
if lst[i - 1] <= lst[i]:
i += 1
... | 32 | import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowercase_ ( unittest.TestCase ):
... | 338 | 0 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCamelCase_( snake_case__: Union[str, Any] , snake_case__: int , snake_case__: Dict )... | 335 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/confi... | 335 | 1 |
def _A ( _lowercase = 1_00_00_00 ) -> int:
"""simple docstring"""
__UpperCamelCase = limit + 1
__UpperCamelCase = [0] * limit
for first_term in range(1 , __A ):
for n in range(__A , __A , __A ):
... | 310 |
from datetime import datetime
import requests
def A (__A : str ) -> bytes:
"""simple docstring"""
UpperCAmelCase_ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
UpperCAmelCase_ = r... | 51 | 0 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
__snake_case : str =datasets.utils.logging.get_logger(__name__)
@dataclass
class lowerCamelCase__ ( dat... | 356 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__snake_case : Optional[int] ={
'configuration_vision_text_dual_encoder': ['VisionTextDualEncoderConfig'],
'processing_vi... | 94 | 0 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = R"""
Args:
input_ids (`torch.LongTensor` of shape... | 92 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
UpperCamelCase__ = get_tests_dir("""fixtures/spiece.mode... | 92 | 1 |
from functools import lru_cache
def __lowerCAmelCase ( a__ ) -> set:
__a = 2
__a = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.add(a__ )
if n > 1:
factors.add(a__ )
return f... | 368 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
A : int = {
'configuration_mobilevit': ['MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileViTConfig', 'MobileViT... | 33 | 0 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
fr... | 61 |
"""simple docstring"""
import numpy as np
def a__ ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase = 1E-12 , lowerCAmelCase = 1_00 , ) -> tuple[float, np.ndarray]:
assert np.shape(lowerCAmelCase )[0] == np.shape(lowerCAmelCase )[1]
# Ensure prope... | 171 | 0 |
def snake_case ( snake_case__ :str , snake_case__ :str) -> Tuple:
assert x is not None
assert y is not None
_A = len(snake_case__)
_A = len(snake_case__)
# declaring the array for storing the dp values
_A ... | 81 | from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi.routing impor... | 81 | 1 |
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case_ = _modexpt(SCREAMING_SNAKE_CASE__ , exponent // 2 , SCREAMING_SNAKE_CASE__ ) %... | 8 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
a__ : Tuple = False
class UpperCamelCase_ ( unittest.Test... | 54 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderb... | 44 |
from sklearn.metrics import mean_squared_error
import datasets
A__ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel, M. and Prettenho... | 44 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 275 |
def _lowercase ( lowercase__ , lowercase__ ):
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def _lowercase ( lowercase__ , lowercase__=0 ):
return sorted(lowercase__ , key=lambda lowercase__ : x[column] )
def _lowercase ( lower... | 275 | 1 |
def UpperCAmelCase_ ( _A ):
'''simple docstring'''
if not isinstance(_A , _A ):
raise TypeError('''Input value must be an \'int\' type''' )
SCREAMING_SNAKE_CASE__ = 0
while number:
position += 1
number >>= 1
return posit... | 218 |
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogram_diffusion import S... | 218 | 1 |
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_vision_available
from ...test_... | 123 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
lowerCamelCase :Union[str, Any] ... | 206 | 0 |
def lowerCamelCase_ ( _UpperCamelCase ) -> list:
"""simple docstring"""
if len(_lowerCamelCase ) <= 1:
return [tuple(_lowerCamelCase )]
snake_case_ : Union[str, Any] = []
def generate(_UpperCamelCase , _UpperCamelCase ):
i... | 370 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/config.json''',
# See all BioGPT models at https://huggingface.... | 279 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class UpperCamelCase_ (__A ):
__magic_name__ = '''WhisperFeatureExtractor'''
__magic_name__ = '''WhisperTokenizer'''
def __init__( self : Tuple , lowerCAmelCase_ : List[Any] , lowerCAm... | 268 |
"""simple docstring"""
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def snake_case ( A__ ,A__ ,A__ ):
if not arr:
return None, None, 0
if low == high:
return low, high, arr[... | 268 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus im... | 324 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
_snake_case = HUGGINGFACE_HUB_CACHE
_snake_case = 'config.json'
_snake_case = 'diffusion_pytorch_model.bin'
_snake_case = 'dif... | 324 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase : Optional[int] = {
'''configuration_funnel''': ['''FUNNEL_PRETRAINED_CONFI... | 318 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__lowercase : Dict = logging.get_logger(__name__)
class __lowercase ( _lowercase ):
def __init__(self , *A , **A ):
warnings.warn(
... | 318 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ : Optional[int] ={
'''configuration_convnext''': ['''CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''C... | 118 |
from collections import deque
from .hash_table import HashTable
class UpperCAmelCase_ ( UpperCamelCase_ ):
'''simple docstring'''
def __init__( self , *_A , **_A ):
'''simple docstring'''
super().__init__(*_A , **_A )
... | 118 | 1 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case = logging.get_logger(__name__)
__snake_case = """https://... | 259 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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, random_attention_mask... | 259 | 1 |
"""simple docstring"""
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCL... | 241 |
"""simple docstring"""
# Copyright 2023 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/licen... | 241 | 1 |
"""simple docstring"""
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from dif... | 84 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__Upp... | 84 | 1 |
def snake_case_ (__A : str , __A : str ) -> list:
__lowerCAmelCase : Tuple = len(__A )
__lowerCAmelCase : Dict = []
for i in range(len(__A ) - pat_len + 1 ):
__lowerCAmelCase : Union[str, Any] = Tru... | 139 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__UpperCAmelCase = logging.get_logger(__name__)
def snake_case_ (__A : List[str] , __... | 139 | 1 |
"""simple docstring"""
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def a_ ( lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase=1_0_2_4 ):
UpperCAmelCase__ , UpperCAmelCase__ ... | 98 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
A =[
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
'text-classification',... | 34 | 0 |
"""simple docstring"""
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
cl... | 353 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowerCamelCase__ = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\... | 310 | 0 |
"""simple docstring"""
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _sna... | 60 |
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 GradientState
from accelerate.test_utils ... | 333 | 0 |
def lowerCAmelCase_ ( UpperCamelCase_ , UpperCamelCase_ ) -> Optional[int]:
return x if y == 0 else greatest_common_divisor(__a , x % y )
def lowerCAmelCase_ ( UpperCamelCase_ , UpperCamelCase_ ) -> Tuple:
return (x * y) // grea... | 350 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_UpperCAmelCase = '\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex and Pr... | 328 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : Any = {'''configuration_fnet''': ['''FNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FNetConfig''']}... | 236 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
... | 71 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolv... | 335 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ... | 335 | 1 |
"""simple docstring"""
import baseaa
def A ( snake_case__ ):
'''simple docstring'''
return baseaa.aaaencode(string.encode("""utf-8""" ) )
def A ( snake_case__ ):
'''simple docstring'''
return baseaa.aaadecode(_SCREAMING_SNAKE_CASE ).deco... | 165 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Tuple = logging.get_logger(__name__)
__A : Optional[Any] = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-... | 260 | 0 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
a_ : str =... | 360 |
'''simple docstring'''
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
a_ : Any = logging.get_logger(__name__)
a_ : Option... | 6 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ : list[float] , snake_case_ : Optional[int] ) -> Tuple:
'''simple docstring'''
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerat... | 1 |
'''simple docstring'''
import math
def UpperCAmelCase_ ( __lowerCamelCase : int ):
lowercase_ :Dict = []
lowercase_ :List[Any] = 2
lowercase_ :Optional[Any] = int(math.sqrt(__lowerCamelCase ) ) # Size of every segment
lowercase_ :Optional... | 223 | 0 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.pro... | 69 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.pro... | 69 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def lowerCAmelCase_ ( snake_case__ ... | 3 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers... | 3 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
... | 322 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar('T')
class lowerCAmelCase__ ( Generic[T] ):
def __init__( self : Union[str, Any]... | 322 | 1 |
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
assert (
isinstance(UpperCamelCase__ , UpperCamelCase__ ) and number_of_steps > 0
), F'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
if number_... | 285 |
def __lowerCamelCase ( ):
'''simple docstring'''
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_UpperCAmelCase : Union[str, Any] = generate_large_matrix()
_UpperCAmelCase : Tuple = (
[[4,... | 285 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a : Optional[Any] = logging.get_logger(__name__)
a : List[str] = {
"""m... | 338 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
a : Dict = logging.get_logger(__name__)
class UpperCamelCase_ ( __magic_name__ ):
def __init__( self , *A , **A ) -> ... | 338 | 1 |
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_confi... | 50 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase , _UpperCAmelCase ) -> list[tuple[int, int]]:
lowerCamelCase__ , lowerCamelCase__ : Union[str, Any] = position
lowerCamelCase__ : Optional[Any] = [
(y + 1,... | 50 | 1 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class _A ( unittest.TestCase ):
def A__ ( self ):
... | 366 | """simple docstring"""
def UpperCAmelCase__ ( lowerCAmelCase__ :int ) -> int:
'''simple docstring'''
if not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise TypeError("""only integers accepted as input""" )
else:
lowercase ... | 32 | 0 |
"""simple docstring"""
import unittest
import numpy as np
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, prepare_image_inputs
... | 45 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
a_ :Optional[Any] = logging.getLogger(__n... | 277 | 0 |
from datetime import datetime
import requests
def lowerCAmelCase_ ( UpperCamelCase_ ) -> bytes:
UpperCamelCase_ = "https://downloadgram.net/wp-json/wppress/video-downloader/video?url="
UpperCamelCase_ = requests.get(base_url + url ).json()[0]["url... | 328 |
def lowerCAmelCase_ ( UpperCamelCase_ ) -> list:
UpperCamelCase_ = int(UpperCamelCase_ )
if n_element < 1:
UpperCamelCase_ = ValueError("a should be a positive number" )
raise my_error
UpperCamelCase_ = ... | 328 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import ceil, floor, sqrt
def __UpperCAmelCase ( UpperCAmelCase_ : int = 2_00_00_00 ) -> int:
'''simple docstring'''
__snake_case : list[int] = [0]
__snake_case : int
... | 172 | """simple docstring"""
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import ded... | 172 | 1 |
"""simple docstring"""
from math import pi, sqrt, tan
def UpperCAmelCase ( UpperCAmelCase ) -> float:
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def UpperCAmelCase ( UpperCAmelCase , Upper... | 312 | """simple docstring"""
__UpperCamelCase = 256
# Modulus to hash a string
__UpperCamelCase = 100_0003
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase ) -> bool:
snake_case_ = len(UpperCAmelCase )
snake_case_ = len(UpperCAmelCase )
if p_len > t_len:
... | 312 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_commo... | 2 | '''simple docstring'''
import os
from math import logaa
def lowerCAmelCase_ ( snake_case_ : str = "base_exp.txt" ) -> int:
'''simple docstring'''
UpperCAmelCase_ = 0
UpperCAmelCase_ = 0
for i, line in enumerate(open(os.path.join(os.path... | 1 | 0 |
'''simple docstring'''
from __future__ import annotations
class A :
def __init__( self , SCREAMING_SNAKE_CASE ) -> Tuple:
"""simple docstring"""
A : Tuple = TypeError(
'''Matrices mu... | 356 |
'''simple docstring'''
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class A ( __snake_case ):
def __init__( self , SCREAMING_SNAKE_CAS... | 311 | 0 |
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,
MaxNewTokensCriteria,... | 248 |
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class A__(a_ ):
"""simple docstring"""
_A : ... | 248 | 1 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _lowercase ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self : List[str] ) -> Optional[Any]:
"""simple docstring"... | 50 | a_ = '\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
a_ = [{'type': 'code', 'content': INSTALL_CONTENT}]
a_ = {
'{processor_class}': 'FakeProcessorClass',
'{model... | 50 | 1 |
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 snake_case__ ( SCREAMING_SNA... | 214 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
from... | 214 | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE ( a_ ):
"""simple docstring"""
lowercase__ = "SpeechT5FeatureExtractor"
lowercase__ = "SpeechT5Tokenizer"
def __init__( self : Optional[Any] ,... | 367 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sq... | 74 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
lowercase : Optional[Any] = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAI... | 42 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelin... | 333 | 0 |
'''simple docstring'''
from __future__ import annotations
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Dict , _UpperCAmelCase : int = 0 ):
"""simple docstring"""
UpperCAmelCase__ = key
def SCREAMING_S... | 61 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {... | 61 | 1 |
import math
__magic_name__: Union[str, Any] = 10
__magic_name__: Union[str, Any] = 7
__magic_name__: Tuple = BALLS_PER_COLOUR * NUM_COLOURS
def UpperCamelCase ( _A = 20 ):
"""simple docstring"""
__magic_name__ : str = math.co... | 342 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class ... | 342 | 1 |
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : str ) -> list[int]:
'''simple docstring'''
return [ord(lowercase__ ) - 96 for elem in plain]
def __UpperCamelCase ( lowercase__ : list[int] ) -> str:
'''simple docstring'''
... | 28 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 1 |
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
_lowerCamelCase : Optional... | 282 |
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 ...tokenization_u... | 282 | 1 |
"""simple docstring"""
import requests
def __A ( __lowerCamelCase , __lowerCamelCase ) -> None:
a = {"""Content-Type""": """application/json"""}
a = requests.post(__lowerCamelCase , json={"""text""": message_body} , ... | 360 |
def __A ( __lowerCamelCase ) -> bool:
if num < 0:
return False
a = num
a = 0
while num > 0:
a = rev_num * 10 + (num % 10)
num //= 10
return num_copy == rev_num
if __name__ == "__main__":
import doctest
doctest.testmod... | 347 | 0 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 321 |
'''simple docstring'''
from timeit import timeit
def lowercase__ ( __UpperCamelCase )-> int:
if number < 0:
raise ValueError("""the value of input must not be negative""" )
UpperCamelCase = 0
while number:
number &= n... | 321 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCamelCase__ = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenization_ctrl""": [... | 182 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase , _UpperCamelCase = None ):
if version.parse(hfh.__version__ ).release < version.parse('0.11.0' ).rel... | 182 | 1 |
"""simple docstring"""
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_tr... | 61 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Con... | 201 | 0 |
"""simple docstring"""
from collections.abc import Generator
def lowercase_ ( ) -> Generator[int, None, None]:
'''simple docstring'''
__lowerCamelCase : List[Any] = 0, 1
while True:
__lowerCamelCase : List[str] = b, a + ... | 351 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
class _snake_case ( a__ ):
snake_case__ = "bert-generation"
def __init__( self : Optional[int] , UpperCAmelCase : Dict=50358 , UpperCAmelCase : int=1024 , U... | 64 | 0 |
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