code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
class _lowerCamelCase :
def __init__( self , lowerCAmelCase = 0 ) -> List[str]:
SCREAMING_SNAKE_CASE__: Tuple= key
def UpperCamelCase_ ( self , lowerCAmelCase , lowerCAmelCase ) -> list[str]:
assert isinstance(lo... | 64 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 0 |
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 SCREAMING_SNAKE_CASE ( a_ ):
"""simple doc... | 218 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( a_ ):
"""simple docstring... | 218 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
... | 38 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__UpperCamelCase : Optional[Any] = '__DUMMY_TRANSFORMERS_USER__'
__UpperCamelCase : Optional[Any] = 'Dummy User'
__UpperCa... | 519 | 0 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
... | 519 |
import sys
UpperCAmelCase_ = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
'''66896648950445244523161731... | 519 | 1 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_availa... | 460 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 135 | 0 |
'''simple docstring'''
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUE... | 344 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/faceb... | 344 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 568 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 568 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase :Any = {
"""configuration_lxmert""": ["""LXMERT_PRETRAINE... | 701 | '''simple docstring'''
import unittest
from transformers import MPNetConfig, 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, ids_tensor, random_atten... | 179 | 0 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property... | 169 |
"""simple docstring"""
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'snap-research/efficientformer-l1-300': (
'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/c... | 169 | 1 |
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 DUMMY_... | 710 |
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
__A : Any = logging.get_logger(__name__)
__A : Dict = {
'hustvl/yolos-small': 'https... | 75 | 0 |
def a__ ( A__, A__ ):
def get_matched_characters(A__, A__ ) -> str:
SCREAMING_SNAKE_CASE_ : Dict = []
SCREAMING_SNAKE_CASE_ : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
SCREAMIN... | 101 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
_A = {
"... | 713 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_A = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6: (3, 2), 7: (7, 1), 8: (4, 2), 9: (3, ... | 279 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase = {
'''configuration_albert''': ['''ALBERT_PRE... | 40 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
# TODO Update this
_lowercase = {
"""facebook/esm-1b""": """https://huggingface.... | 443 | 0 |
"""simple docstring"""
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface... | 194 |
"""simple docstring"""
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torc... | 194 | 1 |
from __future__ import annotations
class lowercase_ :
def __init__( self : List[str] , snake_case__ : str , snake_case__ : str ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = text, patt... | 360 |
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():
... | 360 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_barthez impor... | 701 |
from pathlib import Path
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray ) -> np.ndarray:
__lowercase , __lowercase , __lowercase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_989 * r + 0.5_870 * g + 0.1_140... | 688 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 682 |
"""simple docstring"""
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_avai... | 682 | 1 |
"""simple docstring"""
def A_ ( __lowercase ):
assert column_title.isupper()
UpperCamelCase_ : List[str] =0
UpperCamelCase_ : List[Any] =len(__A ) - 1
UpperCamelCase_ : Any =0
while index >= 0:
UpperCamelCase_ : Tuple =(ord(column_title[i... | 701 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = {
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr-ctx_encoder... | 395 | 0 |
"""simple docstring"""
def __snake_case ( UpperCamelCase__ = 10**9 ) -> int:
"""simple docstring"""
A = 1
A = 2
A = 0
A = 0
A = 0
while perimeter <= max_perimeter:
perimeters_sum += perimeter
... | 690 |
"""simple docstring"""
from __future__ import annotations
def __snake_case ( UpperCamelCase__ ) -> list[int]: # This function is recursive
"""simple docstring"""
A = len(UpperCamelCase__ )
# If the array contains only one element, we return it (it's th... | 690 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"""SenseTime/deformable-detr""": """https://huggingface.co/senseti... | 707 |
"""simple docstring"""
class A__ :
def __init__( self ):
__lowerCAmelCase : Optional[int] = 0
__lowerCAmelCase : Any = 0
__lowerCAmelCase : List[Any] = {}
def __lowerCamelCase ( self , _SCREAMING_SNAKE_CASE ):
if vertex not in self.ad... | 549 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
SCREAMING_SNAKE_CASE_ = (3, 9, -1_1, 0, 7, 5, 1, -1)
SCREAMING_SNAKE_CASE_ = (4, 6, 2, 0, 8, 1_0, 3, -2)
@dataclass
class ... | 597 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE__ ):
__a : List[str] = [
'encoder.version',
'dec... | 597 | 1 |
"""simple docstring"""
def snake_case ( UpperCamelCase__ : Any , UpperCamelCase__ : Union[str, Any] ) -> Optional[int]:
lowerCamelCase : Union[str, Any] = """"""
for i in table:
res += inp[i - 1]
return res
def snake_cas... | 706 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowerCamelCase :str = get_tests_dir... | 42 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers ... | 510 |
'''simple docstring'''
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self , __a = None ):
'''simple docstring'''
__a : list = []
# Stores indexes of each item for supporting updates and deletion.
__a :... | 476 | 0 |
"""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.swit... | 715 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class snake_case :
def __init__( self :Dict , _lowerCamelCase :List[str] ):
__SCREAMING_SNAKE_CASE : Union[str, Any] = str(id_ )
__SCREAMING_SNAKE_CAS... | 401 | 0 |
"""simple docstring"""
import json
from typing import 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_bart ... | 227 |
"""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 ... | 227 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[Any] = logging.get_logger(__name__)
lowerCAmelCase : List[Any] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-... | 533 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = ["note_seq"]
def __init__( self , *_a , **_a ):
"""simple docstri... | 533 | 1 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : List[Any] = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingf... | 578 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDep... | 387 | 0 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def _UpperCAmelCase (UpperCamelCase_ : int ):
'''simple docstring'''
_lowerCAmelCase = prime_factors(_lowerCamelCase )
if is_square_free(_lowerCamelCase ):
r... | 719 |
import numpy as np
def _UpperCAmelCase (UpperCamelCase_ : np.array ):
'''simple docstring'''
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 196 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import T... | 167 | 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 B... | 167 | 1 |
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.transforms.functional import In... | 235 |
def snake_case (UpperCamelCase : list , UpperCamelCase : list , UpperCamelCase : int ):
'''simple docstring'''
lowerCamelCase__ = len(UpperCamelCase )
lowerCamelCase__ = [[0] * n for i in range(UpperCamelCase )]
for i in range(UpperCame... | 235 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_bloom': ['BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BloomConfig', 'BloomOnnxConfig'],
}
try:
if not... | 485 | def lowerCamelCase ( UpperCamelCase : int , UpperCamelCase : int ) -> float:
return base * power(UpperCamelCase , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('Raise base to the power of exponent using recursion...')
A = ... | 544 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerConfig",
],
}
try:
if ... | 658 |
import string
def A ( _lowerCamelCase ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
_lowerCAmelCase : str = ""
for symbol in message:
if symbol in string.asc... | 658 | 1 |
def snake_case__ ( UpperCAmelCase : int ):
if not isinstance(UpperCAmelCase , UpperCAmelCase ):
raise TypeError("only integers accepted as input" )
else:
lowerCAmelCase__ :str = str(abs(UpperCAmelCase ) )
lowerCAmelCa... | 145 |
from math import isclose, sqrt
def snake_case__ ( UpperCAmelCase : float , UpperCAmelCase : float , UpperCAmelCase : float ):
lowerCAmelCase__ :Optional[int] = point_y / 4 / point_x
lowerCAmelCase__ :Tuple = 2 * normal_gradient / (1 + norm... | 145 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_a : List[str] = {
"""configuration_bert""": ["""BERT... | 714 |
"""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_transfo... | 87 | 0 |
'''simple docstring'''
# 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 Versio... | 683 | # NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet import ... | 670 | 0 |
"""simple docstring"""
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
class __UpperCAmelCase :
A__ : ... | 719 | """simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowerCamelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase = None ) -> str:
'''simple docstring''... | 132 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a : Optional[int] = {
'configuration_roformer': ['ROFORMER_PRETRAINED... | 556 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
a : int = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
a : int = _... | 556 | 1 |
'''simple docstring'''
def __UpperCamelCase ( _lowerCAmelCase ):
"""simple docstring"""
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
... | 703 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
__lowerCAmelCase ={
"facebook/maskformer-swin-base-ade": (
"https://hugging... | 405 | 0 |
from __future__ import annotations
import typing
from collections import Counter
def lowerCAmelCase_ ( lowercase: int ) -> typing.Counter[int]:
'''simple docstring'''
_UpperCamelCase: typing.Counter[int] = Counter()
for base in range(1 , max_perimeter + 1 ):
for perp... | 271 | from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def lowerCAmelCase_ ( lowercase: str , lowercase: complex , lowercase: str = "x" , lowercase: float = 10**-10 , lowercase: int = 1 , ) -> complex:
'''simple docstri... | 271 | 1 |
import numpy as np
def a__ (__lowercase :np.ndarray , __lowercase :float ) -> np.ndarray:
return np.where(vector > 0 , __lowercase , (alpha * (np.exp(__lowercase ) - 1)) )
if __name__ == "__main__":
import doctest
doctest.testm... | 332 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase : Dict =logging.get_logger(__name__)
_UpperCamelCase : Optional[Any] ={
'facebook/xmod-bas... | 332 | 1 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __snake_case ( __SCREAMING_SNAKE_CASE , unittest.TestC... | 100 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_lza, require... | 479 | 0 |
'''simple docstring'''
__UpperCAmelCase = frozenset(
[
'prompt',
'height',
'width',
'guidance_scale',
'negative_prompt',
'prompt_embeds',
'negative_prompt_embeds',
'cross_attention_kwargs',
]
)
__UpperCAmelCase = froz... | 220 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def SCREAMING_SNAKE_CASE_ ( snake_case_ : np.ndarray ) -> np.ndarray:
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Optional[Any] ... | 220 | 1 |
def a (lowerCAmelCase__ ):
__a = len(lowerCAmelCase__ )
while cur > 1:
# Find the maximum number in arr
__a = arr.index(max(arr[0:cur] ) )
# Reverse from 0 to mi
__a = arr[mi::-1] + arr[mi + 1 : len(lowerCAmelCase__ )]
# Reverse whole list
... | 99 |
'''simple docstring'''
def __snake_case ( ):
lowerCamelCase_ = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
lowerCamelCase_ = 6
lowerCamelCase_ = 1
lowerCamelCase_ = 1901
lowerCamelCase_ = 0
while year < 2001:
day += 7
if (year % 4 == 0 an... | 675 | 0 |
_lowerCAmelCase = [
"DownloadConfig",
"DownloadManager",
"DownloadMode",
"StreamingDownloadManager",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
| 71 | from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _snake_case ( __snake_case , __snake_case , __snake_case = 1 / sqrt(2 ) ):
_UpperCamelCase = tau * frequency / samplerate
_UpperCamelCase = sin(__snake_case )
_UpperCamelCase ... | 71 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepa... | 8 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 1 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class _a ( SCREAMING_SNAKE_CASE__ ):
"""simple ... | 719 |
'''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
... | 220 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Token... | 24 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, slow
... | 410 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __lowercase ( unittest.TestCase ):
def ... | 711 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__lowercase : int = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 357 | 0 |
SCREAMING_SNAKE_CASE__ = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def A ( __UpperCamelCase ) -> int:
A__ = 0
while number:
# Increased Speed Slightly by checking every 5 digits together.
sum_of_digits_squared += DIGITS_SQUARED[numb... | 9 |
'''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import Backbone... | 418 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
"configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
"tokenization_luke": ["LukeTokenizer"],
}
try:
if not is_torch_available():
raise ... | 583 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
FEATURE_... | 583 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
f... | 382 |
import argparse
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_dummies.py
lowerCamelCase__ = '''src/diffusers'''
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(r''... | 381 | 0 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 720 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class A_ :
def __init__( self : List[str] , snake_case__ : Union[str, Any] ):
lowercase = data
lowercase = [0X6_7_4_5_2_3_0_1, 0Xe_f_c_d_a_b... | 72 | 0 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
UpperCamelCase__ :Union[str, Any] = Fal... | 355 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVec... | 355 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase : Any = logging.get_logger(__name__)
__UpperCAmelCase : Any = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
# See all BioGPT models at http... | 704 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase : str = logging.get_logger(__name__)
__UpperCAmelCase : List[Any] = {
'YituTech/conv-bert-ba... | 249 | 0 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
fro... | 611 |
class a :
def __init__( self : Union[str, Any] , snake_case__ : str ):
"""simple docstring"""
__lowerCAmelCase = arr.split("," )
def UpperCAmelCase__ ( self : str ):
"""simple docstring"""
__lowerCAmelCase ... | 611 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCamelCase = {
'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
'configuration_maskformer_swin'... | 713 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCamelCase__ ( UpperCAmelCase ):
"""simple docstring"""
@staticmethod
@abstractmethod
def snake_case__ ( snake_case ):
'''simple docstring'''
raise NotImp... | 185 | 0 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase ( _UpperCAmelCase ):
lowerCamelCase : List[Any] = (DDIMParallelScheduler,)
lowerCamelCase : Union[str, Any] = (('''eta''', 0.0), ('''num_inference_st... | 35 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :int ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive""" )... | 504 | 0 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE: list[int] , SCREAMING_SNAKE_CASE: str ):
"""simple docstring"""
_lowerCAmelCase = int(SCREAMING_SNAKE_CASE )
# Initialize Result
_lowerCAmelCase = []
... | 491 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_avai... | 491 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
A__ : Dict = 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: E402
# This is the refere... | 183 |
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_... | 183 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
i... | 711 |
from collections import deque
from .hash_table import HashTable
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : Dict , *__UpperCamelCase : Tuple , **__UpperCamelCase : List[Any] ) -> Union[str, Any]:
super().__init__(*__UpperC... | 224 | 0 |
"""simple docstring"""
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_configuratio... | 636 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : Tuple =(... | 636 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import... | 625 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def snake_case__ ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =x
lowerC... | 625 | 1 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def __a ( _UpperCamelCase: Any , _UpperCamelCase: Optional[int] , _UpperCamelCase: List[Any] , _UpperCamelCase: List[str] ) -> Tuple:
"""simple docstring"""
... | 185 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
__UpperCamelCase : Union[str, Any] = logging.getLogger(__name__)
class __UpperCamelCase ( _lowerCAmelCase ):
... | 80 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"
),
# See all Vivit models ... | 720 | from __future__ import annotations
from collections import deque
class __lowercase :
def __init__( self : Dict , __lowerCamelCase : list[str] ) -> List[str]:
'''simple docstring'''
lowercase = []
self.adlis... | 479 | 0 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
snake_case_ : Optional[Any] = '''
import os
'''
snake_case_ : Optional[Any] = '''
def foo():
import os
return False
'''
snake_case_ : str = '''
def fo... | 138 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common... | 450 | 0 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
UpperCamelCase__ ='docs/source/en/_toctree.yml'
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Any = defaultdict(snake_case__ )
for doc in model_doc:
... | 706 |
def lowerCamelCase__ (__lowerCamelCase = 10**9 ):
_SCREAMING_SNAKE_CASE : List[str] = 1
_SCREAMING_SNAKE_CASE : Any = 2
_SCREAMING_SNAKE_CASE : List[Any] = 0
_SCREAMING_SNAKE_CASE : Dict = 0
_SCREAM... | 381 | 0 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __magic_name__ (unittest.TestCase ):
'''simple docstring'''
... | 33 |
from copy import deepcopy
class __magic_name__ :
'''simple docstring'''
def __init__( self:int , _a:list[int] | None = None , _a:int | None = None ):
if arr is None and size is not None:
snake_case__ = size
snake_case__ = ... | 33 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: str = logging.get_logger(__name__)
A: Optional[Any] = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json",
}
class ... | 713 |
"""simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
A: List[An... | 359 | 0 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table impor... | 317 |
def snake_case_ (__A : list[int] , __A : list[int] ) -> None:
__lowerCAmelCase : Union[str, Any] = len(__A )
print("""The following activities are selected:""" )
# The first activity is always selected
__lowerCAmelCase : str = 0
print(__A ... | 651 | 0 |
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class snake_case_ :
"""simple docstring"""
pass
| 455 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case_ (lowercase__ ):
"""simple docstring"""
_lowerCamelCase = """ClapFeatureExtractor"""
_lowerCamelCase = ("""RobertaTokenizer""", """RobertaTokeniz... | 455 | 1 |
"""simple docstring"""
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
f... | 238 |
"""simple docstring"""
import argparse
import datetime
def UpperCamelCase ( _lowerCAmelCase : str ) -> str:
_UpperCAmelCase : List[str] = {
"""0""": """Sunday""",
"""1""": """Monday""",
"""2""": """Tuesday""",
"""3""": """We... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE_ : Any = TypeVar('T')
class a ( Generic[T] ):
"""simple docstring"""
def __init__( self: List[str] , UpperCamel... | 500 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_ : Any = {
'configuration_jukebox': [
'JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP',
'JukeboxConfig',
... | 500 | 1 |
from datetime import datetime as dt
import os
from github import Github
A : Optional[Any] = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def UpperCamelCase__ ( ) -> Dict:
_... | 287 |
"""simple docstring"""
from maths.prime_check import is_prime
def _snake_case ( snake_case__ : int ):
if not isinstance(snake_case__ , snake_case__ ):
A = F'Input value of [number={number}] must be an integer'
raise TypeError(snake_case__ )
if is_prime(snake_case__ ) and is_prime(... | 91 | 0 |
'''simple docstring'''
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,
... | 708 | '''simple docstring'''
import re
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple docstring'''
return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def __lowerCamelCase ( _UpperCamelCase : str ):
'''simple d... | 43 | 0 |
def a (lowerCAmelCase__ ):
if number < 0:
raise ValueError("""number must not be negative""" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 99 |
"""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,
)
| 624 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 713 | import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def A__ ( __A ):
'''simple docstring'''
_lowerCamelCase : Tuple = {}
... | 15 | 0 |
'''simple docstring'''
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class A__ ( UpperCamelCase ):
"""simple docstring"""
def __init__( self : Any , lowerCAmelCase... | 494 | '''simple docstring'''
def __UpperCAmelCase ( a_: int ):
if not isinstance(a_, a_ ):
_UpperCAmelCase : List[str] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(a_ )
if number < 0:
return False
_UpperCAmelCase : Unio... | 494 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
Wa... | 213 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torc... | 213 | 1 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
a : Optional[int] = logging.getLogger(__name__)
@dataclass
class _a ( _lowerCAmelCase ... | 556 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
class _a ( _lowerCAmelCase ):
A = '''timm_backbone'''
def __init__(self, SCREAMING_SNAKE_CASE_=None, SCREAMING_SNAKE... | 556 | 1 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipelin... | 703 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer... | 123 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 30 |
from __future__ import annotations
def __a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> list[str]:
'''simple docstring'''
if nth_term == "":
return [""]
__UpperCAmelCase = int(SCREAMING_SNAKE_CASE )
__UpperCAmelCase ... | 303 | 0 |
"""simple docstring"""
from math import pi, sqrt, tan
def __snake_case ( SCREAMING_SNAKE_CASE: float ):
"""simple docstring"""
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
r... | 491 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, 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, ids_tensor, random_attenti... | 491 | 1 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def __A (_SCREAMING_SNAKE_CASE ) ->int:
"""simple docstring"""
lowerCAmelCase__ :List[Any] = [
'decoder.... | 93 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
_UpperCa... | 284 | 0 |
"""simple docstring"""
def A_ ( _lowerCAmelCase : Union[str, Any] ):
"""simple docstring"""
_a = [0] * len(_lowerCAmelCase )
_a = []
_a = []
_a = 0
for values in graph.values():
for i in values:
... | 285 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowerCamelCase ( a__ ):
'''simple docstring'''
A_ : Optional[int] = ['image_processor', 'tokenizer']
A_ : Union[str, ... | 285 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"""facebook/xmod-base""": """https://huggi... | 29 |
'''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_... | 369 | 0 |
"""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
from .... | 674 | """simple docstring"""
import os
from math import logaa
def _UpperCAmelCase ( lowerCamelCase__ = "base_exp.txt" ):
"""simple docstring"""
lowerCAmelCase__ = 0
lowerCAmelCase__ = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(lowerCamelCase__ ... | 674 | 1 |
'''simple docstring'''
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_... | 349 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase = "cpu" , _lowerCamelCase = None ) -> None:
'''simple docstring'''
_lowerCamelCase : Any = torch.loa... | 46 | 0 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
_snake_case : Dict = True
except (ImportError, ModuleNotFoundError):
_snake_case : Union[str, Any] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', quiet=True)
... | 718 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTok... | 524 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def UpperCAmelCase ( snake_case : Union[str, Any] = None ):
if nums is None or not nums:
raise ValueError('''Input sequence should not be empty''' )
_lowerCAmelCase:Optional[int] = nums[0]
... | 227 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_pr... | 207 | 0 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils i... | 95 |
"""simple docstring"""
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowercase ( _SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
def is_in_circle(_SCREAMING_SNAKE_... | 95 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A ( SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def lowercase ( A_ : ArgumentParser ) -> ... | 564 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
SCREAMING_SNAKE_CASE: Optional[int] = 2_9_9_7_9_2_4_5_8
# Symbols
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE: ... | 360 | 0 |
'''simple docstring'''
import numpy as np
import qiskit
def _SCREAMING_SNAKE_CASE ( A : int = 8 , A : int | None = None ) -> str:
"""simple docstring"""
__snake_case : str = np.random.default_rng(seed=A )
... | 709 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
res... | 61 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_a = logging.get_logger(__name__)
_a = "▁"
_a = {"vocab_file": "spiece.model"}
_a ... | 481 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 481 | 1 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFor... | 703 |
"""simple docstring"""
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures... | 505 | 0 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTe... | 39 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''huggingface/informer-tourism-monthly''': (
'''https://huggingface.co/hug... | 39 | 1 |
"""simple docstring"""
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaT... | 645 | """simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vi... | 645 | 1 |
"""simple docstring"""
import enum
import shutil
import sys
snake_case , snake_case = shutil.get_terminal_size()
snake_case = {'''UP''': '''A''', '''DOWN''': '''B''', '''RIGHT''': '''C''', '''LEFT''': '''D'''}
class UpperCAmelCase ( enum.Enum ):
... | 103 |
from PIL import Image
def A__ ( _a : Image , _a : float ):
'''simple docstring'''
def brightness(_a : int ) -> float:
return 128 + level + (c - 128)
if not -2_5_5.0 <= level <= 2_5_5.0:
raise ValueError("""level must be between -255.0 (black) and... | 385 | 0 |
"""simple docstring"""
from math import isclose, sqrt
def _a ( _snake_case , _snake_case , _snake_case ):
"""simple docstring"""
UpperCAmelCase = point_y / 4 / point_x
UpperCAmelCase = 2 * normal_gradient / (1 + normal_gradient * normal_grad... | 74 |
"""simple docstring"""
import math
def _a ( _snake_case ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all... | 74 | 1 |
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 ... | 79 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=a_ )
class lowerCAmelCase_ ( a_ ):
__UpperCAmelCase = field(default='imag... | 349 | 0 |
def __UpperCamelCase ( _lowerCAmelCase ) -> List[Any]:
"""simple docstring"""
A : Union[str, Any] = [int(lowerCamelCase_ ) for i in ip_va_address.split(""".""" ) if i.isdigit()]
return len(lowerCamelCase_ ) == 4 and all(0 <= int(lowerCamelCase_ ) <= 254 for octet in oct... | 712 |
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead."""
)
| 520 | 0 |
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