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 |
|---|---|---|---|---|
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_m... | 225 |
class SCREAMING_SNAKE_CASE :
def __init__( self : List[Any] ):
'''simple docstring'''
__a = {} # Mapping from char to TrieNode
__a = False
def UpperCamelCase_ ( self : Dict , __lowercase : list[str] ):
... | 225 | 1 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase_ = Lock()
def __magic_name__ ( lowercase , lowercase , lowercase , lowercase , lowerc... | 436 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def __magic_name__ ( lowercase ) -> Union[str, Any]:
"""simple doc... | 436 | 1 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowercase : List[Any] = """src/transformers"""
# Matches is_xxx_available()
lowercase : List[str] = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowercas... | 336 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase : List[str] = {
"""configuration_clip""": [
"... | 336 | 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... | 252 |
import math
from numpy import inf
from scipy.integrate import quad
def snake_case__ ( lowerCAmelCase_ ):
"""simple docstring"""
if num <= 0:
raise ValueError('math domain error' )
return quad(lowerCAmelCase_, 0, lowerCAmelCase_, args=(lower... | 252 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : str =logging.get_logger(__name__)
__lowerCAmelCase : Any ={
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class _lowercase ( A__ ):... | 696 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Dict =logging.get_logger(__name__)
__lowerCAmelCase : List[Any] ={
'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json',
}
class _... | 696 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A__ = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
"""tokenization_mvp""": ["""M... | 717 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A__ = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Layo... | 49 | 0 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_model... | 78 |
"""simple docstring"""
# 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.pipeline_flax_controlnet import FlaxStableDiffus... | 260 | 0 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
UpperCAmelCase : Any = 6378137.0
UpperCAmelCase : str = 6356752.314245
UpperCAmelCase : Tuple = 6_37_81_37
def _SCREAMING_SNAKE_CASE ( a , a ... | 77 |
import copy
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
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 1 |
"""simple docstring"""
def _snake_case ( snake_case__ : int = 100 ):
A = n * (n + 1) * (2 * n + 1) / 6
A = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__main__":
print(F"""{solution() = }""") | 91 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( _lowerCamelCase, _lowerCamelCase, _lowerCamelCase, ) ->tuple:
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("You cannot supply more o... | 575 | 0 |
from ... import PretrainedConfig
a : Union[str, Any] = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class a ( _lowerCamelCase ):
snake_case_ = NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
snake_case_ ... | 711 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[Any] = {
'configuration_mobilevit': ['MOBILEVIT_PRETRAINED_CONFIG_ARCHI... | 593 | 0 |
import sys
import turtle
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : tuple[float, float] , UpperCAmelCase_ : tuple[float, float] ) -> Optional[Any]:
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : tuple[floa... | 443 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 0 |
"""simple docstring"""
def A ( snake_case__ ):
'''simple docstring'''
if not isinstance(snake_case__ , snake_case__ ):
SCREAMING_SNAKE_CASE__ = f"""Input value of [number={number}] must be an integer"""
raise TypeError(snake_case__ )
... | 721 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torc... | 616 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
# See all CANINE models at https://huggingface.co/models?filter=canine
}
class ... | 393 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase :List[str] = logging.get_logger(__name__)
lowerCamelCase :Any = {
'vocab_file': 'vocab... | 487 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
loggin... | 704 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""post_extract_proj""": """feature_projection.projecti... | 531 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
_UpperCamelCase : Optional[int] =argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'
... | 206 |
from PIL import Image
def a__ (__lowercase :Image , __lowercase :float ) -> Image:
def brightness(__lowercase :int ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
raise ValueError('''level must be between -255.... | 206 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( lowerCamelCase_ , lowerCamelCase_) -> bool:
UpperCamelCase__ : Dict = len(lowerCamelCase_)
UpperCamelCase__ : Dict = len(lowerCamelCase_)
UpperCamelCase__ : Dict = [[... | 6 |
'''simple docstring'''
import numpy as np
from PIL import Image
def __UpperCAmelCase ( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_) -> np.ndarray:
UpperCamelCase__ : List[Any] = np.array(lowerCamelCase_)
if arr.s... | 6 | 1 |
from __future__ import annotations
from collections.abc import Callable
def A_ ( A__ , A__ , A__ , A__ = 100 , ) -> Any:
a__ : List[str] = x_start
a__ : int = fnc(__a )
a__ : str = 0.0
for _... | 302 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import pat... | 626 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ : List[Any] = {
'''configuration_clipseg''': [
'''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''CLIPSegConfig''',
... | 702 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class snake_case_( a__ ):
pass
class snake_case_:
def __init__( self : Any , UpperCamelCase_ : Any ):
lowerCAmelCase : Any = data
lowerCAmelCa... | 637 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCam... | 12 |
"""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 ja... | 123 | 0 |
from __future__ import annotations
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not nums:
return 0
snake_case__ : List[Any] = nums[0]
snake_case__ : str = 0
for num in nums[1:]:
snake_case__ , snake_case_... | 127 |
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
lowercase_: Union[str, Any] = logging.get_logger(__name__)
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if isinstance(UpperCAmelCase_ , ... | 127 | 1 |
'''simple docstring'''
import math
def lowerCAmelCase ( UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = [True] * n
__UpperCAmelCase = False
__UpperCAmelCase = False
__UpperCAmelCase = True
... | 262 | '''simple docstring'''
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase ( UpperCamelCase__ : Optional[int] , UpperCamelC... | 262 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_uti... | 720 |
"""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
from ..auto import CONFIG_MAPPING
A__ : Union[str, Any] = logging.... | 660 | 0 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compu... | 594 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowe... | 594 | 1 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, p... | 718 |
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is_tf_available() and ... | 455 | 0 |
from typing import Any
def _A ( SCREAMING_SNAKE_CASE : list , SCREAMING_SNAKE_CASE : list , SCREAMING_SNAKE_CASE : dict , SCREAMING_SNAKE_CASE : dict , SCREAMING_SNAKE_CASE : dict , ):
"""simple docstring"""
_validation(
SCREAMING_SNAKE_CASE_ ... | 563 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing... | 386 | 0 |
'''simple docstring'''
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 lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
... | 716 |
'''simple docstring'''
from __future__ import annotations
import requests
__snake_case : Union[str, Any] = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category c... | 687 | 0 |
# 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 a... | 89 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ ) -> Optional[int]:
# Initialise ... | 89 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import... | 709 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import... | 273 | 0 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__magic_name__ )
class lowerCAmelCase__ ( __magic_name__ ):
'''simple docstring'''
lowercase_ = field... | 184 |
from __future__ import annotations
from statistics import mean
def a ( A__ : list[int] , A__ : list[int] , A__ : int ) -> list[int]:
"""simple docstring"""
_lowercase =[0] * no_of_processes
_lowercase =[0] * no_of_processes
... | 291 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowerCAmelCase__ = {
"configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
"tokenization_gp... | 718 | from __future__ import annotations
from collections import Counter
from random import random
class _a :
"""simple docstring"""
def __init__( self ):
_lowercase ={}
def __lowerCAmelCase ( self , lowerCAmelCase_ ):
_lowercase ={}
def __lowerCAmelCase ( ... | 594 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mob... | 66 |
'''simple docstring'''
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...... | 597 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
'''configuration_funnel''': ['''FUNNEL_PRETRAINED_CONF... | 491 |
"""simple docstring"""
from pathlib import Path
import numpy as np
from PIL import Image
def __snake_case ( SCREAMING_SNAKE_CASE: np.ndarray ):
"""simple docstring"""
_lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase = rgb[:, :, 0], rgb[:... | 491 | 1 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__snake_case = ''''''
__snake_case = ''''''
__snake_case = ''''''
__snake_case = 1 # (0 is vertical, 1 is horizontal)
def _A ( ) -> None... | 1 |
from collections.abc import Generator
from math import sin
def _A ( _lowercase ) -> bytes:
"""simple docstring"""
if len(_lowercase ) != 32:
raise ValueError('Input must be of length 32' )
__UpperCamelCase = B''
for i in [3, 2, 1, 0]:
... | 1 | 1 |
import logging
from transformers import PretrainedConfig
_lowercase: Any = logging.getLogger(__name__)
_lowercase: Optional[Any] = {
'''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json''',
}
class ... | 225 | import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils impor... | 225 | 1 |
import os
import numpy
import onnx
def UpperCAmelCase__( __UpperCAmelCase : str , __UpperCAmelCase : Optional[Any] ):
__snake_case : int = a.name
__snake_case : Dict = b.name
__snake_case : str = ''
__snake_cas... | 576 |
from __future__ import annotations
def __UpperCAmelCase ( lowerCamelCase_ : list[float] ) -> float:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = 0.0_0
SCREAMING_SNAKE_CASE_ : Tuple = 0
for resistor in resistors:
if... | 105 | 0 |
from importlib import import_module
from .logging import get_logger
lowerCAmelCase__ = get_logger(__name__)
class snake_case__:
"""simple docstring"""
def __init__( self : int , SCREAMING_SNAKE_CASE : Any , SCREAMING_SNAKE_CASE : Optional[An... | 703 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 81 | 0 |
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_visio... | 556 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenize... | 556 | 1 |
"""simple docstring"""
from collections import namedtuple
import requests
from lxml import html # type: ignore
a_ = namedtuple('covid_data', 'cases deaths recovered')
def __UpperCAmelCase ( __UpperCamelCase = "https://www.worldometers.info/coronavirus/" ):
... | 523 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase_ ... | 523 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a__ : str = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
""... | 589 |
"""simple docstring"""
import numpy as np
def A__ ( __lowerCamelCase ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 589 | 1 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__a = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__a = [file for file in filepaths if file != file.lower()]
if upper_fi... | 712 |
def UpperCamelCase_ ( a_ = 6008_5147_5143 ) ->int:
try:
A =int(a_ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
raise ValueError("Parameter n must be greater than or equal to one." )
A =2
A =0
if n == 2:
r... | 689 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_mode... | 46 |
"""simple docstring"""
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
@requ... | 46 | 1 |
'''simple docstring'''
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 710 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
... | 39 | 0 |
from __future__ import annotations
from statistics import mean
def a__ ( snake_case , snake_case , snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Tuple = [0] * no_of_processes
__SCREAMING_SNAKE_CASE : List[str] = [0] * no_of_proces... | 74 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCAmelCase : List[Any] = {
'''configuration_layoutlmv2''': ['''LAYOUT... | 107 | 0 |
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 __snake_case ( unittest.TestCase ):
"""simple do... | 712 |
import pytest
_lowercase = '''__dummy_dataset1__'''
_lowercase = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = {"train": REPO_URL + "wikiann-bn-train.jsonl", "validation": REPO_URL + "wikiann-bn-valida... | 683 | 0 |
import numpy as np
def a__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ):
SCREAMING_SNAKE_CASE_ = int(np.ceil((x_end - xa) / h ) )
SCREAMING_SNAKE_CASE_ = np.zeros((n + 1,) )
SCREAMING_SNAKE_CASE_ = ya
... | 140 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class a ( __UpperCAmelCase , unittest.TestCase ):
lowerca... | 611 | 0 |
import math
import tensorflow as tf
from packaging import version
def A_ ( _lowerCAmelCase ) -> Any:
UpperCamelCase : List[Any] = tf.convert_to_tensor(_lowerCAmelCase )
UpperCamelCase : Any = 0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0 ) , x.dtype )... | 38 |
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_video_inputs
if is_torch_available():
import t... | 38 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase_ = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 498 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCamelCase_ = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig... | 498 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils... | 710 |
'''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
... | 411 | 0 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test... | 243 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 ... | 58 | 0 |
"""simple docstring"""
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
SCREAMING_SNAKE_CASE : Union[str, Any] = (
"""This... | 702 |
"""simple docstring"""
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowercase ( _snake_case : Optional[Any] ) ->Any:
"""simple docstring"""
return x + 2
class _UpperCAmelCase ( unittest.T... | 229 | 0 |
"""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_... | 46 |
import math
def a__ ( _UpperCamelCase : float ,_UpperCamelCase : float ):
if (
not isinstance(_UpperCamelCase ,(int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError('''power_factor must be a valid float value between -1 and ... | 175 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : Optional[Any] = logging.get_logger(__name__)
A_ : str ... | 696 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
A_ : Dict = logging.get_logger(__name__) # pylint: disable=invalid-name
class a_ ( snake_c... | 696 | 1 |
def __snake_case ( lowerCAmelCase_ = 1_0**9 ) -> int:
SCREAMING_SNAKE_CASE__ = 1
SCREAMING_SNAKE_CASE__ = 2
SCREAMING_SNAKE_CASE__ = 0
SCREAMING_SNAKE_CASE__ = 0
SCREAMING_SNAKE_CASE__ = 0
while perimeter ... | 100 |
import torch
from torch import nn
class __snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self , A_ , A_ , A_ , A_ , A_=1 , A_=False ):
'''simple docstring'''
super().__init__()
SCREAMING_SNAKE_CASE_... | 100 | 1 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
if not all(char in '''01''' for char in bin_string ):
raise ValueError('''Non-binary value was passed to the function''' )
if not bin_string:
... | 95 |
"""simple docstring"""
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 low... | 95 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderCo... | 525 |
'''simple docstring'''
from __future__ import annotations
lowerCAmelCase = list[tuple[int, int]]
lowerCAmelCase = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, ... | 525 | 1 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class _lowerCamelCase ( unittest.TestCase ):
def UpperCamelCase_ ( self ) -> Dict:
SCREAMING_SNAKE_CASE_... | 107 | import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import (
... | 107 | 1 |
'''simple docstring'''
def A_ ( ) -> Union[str, Any]:
__SCREAMING_SNAKE_CASE : str = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
__SCREAMING_SNAKE_CASE : int = 6
__SCREAMING_SNAKE_CASE : List[Any] = 1
__SCREAMING_SNAKE_CASE... | 158 |
from sklearn.metrics import recall_score
import datasets
__SCREAMING_SNAKE_CASE ="""
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is the true positives and FN is the fa... | 234 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
a__ : str = logging.get_logger(__name__)
class lowercase_ ( a__ ):
def __init__( self , *a , **a ):
war... | 223 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( __A , __A ) -> Optional[int]:
'''simple docstring'''
if len(__A ) <= 1 or n <= 1:
return
insert_next(__A , n - 1 )
rec_insertion_sort(__A , n - 1 ... | 223 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Optional[Any] = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''InstructBlip... | 639 |
def lowercase_ ( _UpperCamelCase ):
'''simple docstring'''
__lowercase = hex_num.strip()
if not hex_num:
raise ValueError('''No value was passed to the function''' )
__lowercase = hex_num[0] == '''-'''
if is_negative:
__lowercase = hex_num[1:]
tr... | 639 | 1 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer,... | 706 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils import logging
... | 413 | 0 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE__ ( UpperCAmelCase__ ):
__lowerCAmelCase : Dict = ['image_processor', 'tokenizer']
__lowerCAmelCase : str = 'AutoImageProce... | 160 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A: int = logging.get_logger(__name__)
A: str = ... | 160 | 1 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
BertTokenizerFast,
... | 383 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"vocab_file": "vocab.json",
"merg... | 383 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase = {
"""configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfig"""],
... | 174 |
"""simple docstring"""
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {name: getattr(transformers,... | 174 | 1 |
# 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/licenses/LICENSE-2.0
#
# Unless r... | 534 |
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class SCREAMING_SNAKE_CASE_ :
__magic_name__: float
__magic_name__: TreeNode | None = None
__magic_name__: TreeNode | None = None
def SCREAMING_SNAKE_CASE_... | 534 | 1 |
"""simple docstring"""
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCamelCase__ ( _a ):
a : Dict = """EncodecFeatureExtractor"""
a : str = ("""T5T... | 616 |
"""simple docstring"""
from PIL import Image
def lowerCAmelCase_ ( UpperCamelCase__ : Image , UpperCamelCase__ : int ):
"""simple docstring"""
__lowercase = (259 * (level + 255)) / (255 * (259 - level))
def contrast(UpperCamelCase__ ... | 616 | 1 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils i... | 719 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( __snake_case : list[int] ):
'''simple docstring'''
if len(__snake_case ) == 0:
return array
lowercase , lowercase = min(__snake_case ), max(__snake_case )... | 134 | 0 |
import qiskit
def __lowerCAmelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int ) -> qiskit.result.counts.Counts:
lowerCamelCase_ = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
... | 272 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase = {'''UserAgent''': UserAgent().random}
def __lowerCAmelCase ( UpperCAmelCase__ : Optional[int] ) -> dict:
lowerCamelCase_ ... | 272 | 1 |
"""simple docstring"""
import doctest
from collections import deque
import numpy as np
class UpperCAmelCase_ :
def __init__( self ) -> None:
__lowercase : int = [2, 1, 2, -1]
__lowercase : Optional[int] = [1, 2, 3, 4]
def _lowerCame... | 523 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Union[str, Any] = list_of_points
# Degree determines... | 523 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class __a :
__snake_case : int
__snake_case : Node | None = None
__snake_case : Node | None = None
... | 600 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : str = logging.get_logger(__name__)
a : Union[str, Any] = {
"microsoft/git-base": "https://huggingface.co/microsoft/git-base... | 63 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_co... | 650 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...image_uti... | 650 | 1 |
'''simple docstring'''
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,
... | 435 | '''simple docstring'''
from sklearn.metrics import fa_score
import datasets
lowerCAmelCase_ : int = """
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
"""
lowerCAmelCase_ ... | 435 | 1 |
def _SCREAMING_SNAKE_CASE ( __snake_case , __snake_case ) -> int:
while a != 0:
_UpperCAmelCase , _UpperCAmelCase = b % a, a
return b
def _SCREAMING_SNAKE_CASE ( __snake_case , __snake_case ) -> int:
if gcd(__snake_case , __snake_c... | 709 |
from collections import deque
from math import floor
from random import random
from time import time
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self : Any ) -> int:
"""simple docstring"""
_UpperCAmelCase = {}
def lowerCamelCase ... | 402 | 0 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipe... | 106 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
from ... import Pr... | 36 | 0 |
from __future__ import annotations
from statistics import mean
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: list[int] , __lowerCamelCase: list[int] , __lowerCamelCase: int ):
'''simple docstring'''
lowercase_ = [0] * no_of_processes
lowercase_ = [0] * no_of_proce... | 601 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
SCREAMING_SNAKE_CASE__ = _LazyModule(__na... | 601 | 1 |
'''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 snake_case ( uni... | 294 |
'''simple docstring'''
def _UpperCamelCase ( lowerCAmelCase__: int ,lowerCAmelCase__: int ) -> str:
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
SCREAMING_SNAKE_CASE_ = str(bin(lowerCAmelCase__ ) )[2:] # ... | 294 | 1 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...ut... | 719 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, id... | 380 | 0 |
from __future__ import annotations
def lowercase_ (A : list[int] , A : int ):
snake_case__ : list[list[int]] = []
snake_case__ : list[int] = []
snake_case__ : List[Any] = 0
snake_case__ : int... | 478 |
from ....utils import logging
a_ :Optional[int] = logging.get_logger(__name__)
class snake_case__ ( lowerCAmelCase_ ):
"""simple docstring"""
def __init__( self : Optional[Any], _snake_case : List[str], _snake_case : Any=None, _snake_case : Tu... | 478 | 1 |
'''simple docstring'''
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
__UpperCAmelCase = "src/transformers"
__UpperC... | 720 |
'''simple docstring'''
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
__UpperCAmelCase = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE :
''... | 692 | 0 |
def A__ ( SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ) -> str:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
_UpperCAmelCase = str(bin(SCREAMING_SNAKE_C... | 32 |
from math import sqrt
def A__ ( SCREAMING_SNAKE_CASE_ : int ) -> bool:
"""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 mult... | 32 | 1 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="""%(message)s""")
def UpperCamelCase ( snake_case__ : np.ndarray ):
'''simple docstring'''
return input_array.r... | 714 |
import math
lowerCamelCase__ = 10
lowerCamelCase__ = 7
lowerCamelCase__ = BALLS_PER_COLOUR * NUM_COLOURS
def UpperCamelCase ( snake_case__ : int = 20 ):
'''simple docstring'''
__snake_case :Dict = ... | 291 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_... | 646 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 1 |
import os
import time
import numpy as np
import onnxruntime as ort
lowercase_: List[Any] = '''1'''
lowercase_: Tuple = '''0'''
lowercase_: Optional[int] = '''1'''
lowercase_: Union[str, Any] = ort.SessionOptions()
lowercase_: List[str] = ort... | 710 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_: int = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransformerConfig',
... | 127 | 0 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
lowercase : str = '''2.13.1'''
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('''3.7'''):
... | 568 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we had to include /home/... | 568 | 1 |
"""simple docstring"""
from typing import Any
class UpperCamelCase :
def __init__( self ,__UpperCamelCase ) -> Tuple:
'''simple docstring'''
lowercase_ : Any = data
lowercase_ : Optional[int] = None
class UpperCamelCase... | 477 | """simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowercase__( ):
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print('Key files generation... | 477 | 1 |
def __UpperCAmelCase ( __a : int ,__a : int ,__a : int ) -> Optional[int]:
"""simple docstring"""
_a : List[Any] = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total... | 14 |
'''simple docstring'''
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ft... | 588 | 0 |
class snake_case ( __SCREAMING_SNAKE_CASE ):
pass
class snake_case ( __SCREAMING_SNAKE_CASE ):
pass
class snake_case :
def __init__(self ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = [
[],
... | 721 |
"""simple docstring"""
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,
... | 628 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Option... | 275 |
'''simple docstring'''
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__A : Tuple = 10
def UpperCamelCase_ ( A__ : ... | 275 | 1 |
def __lowercase ( UpperCAmelCase__ = 600_851_475_143 ):
"""simple docstring"""
try:
__lowerCAmelCase = int(UpperCAmelCase__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
... | 704 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechConfig''']}
t... | 102 | 0 |
'''simple docstring'''
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transfo... | 495 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team and The OpenBMB 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/l... | 495 | 1 |
'''simple docstring'''
from ... import PretrainedConfig
__a = {
"sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class UpperCAmelCase_ ( _a ):
"""simple docstring"""
lowercase = NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
... | 707 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
"configuration_blip_2": [
"BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Blip2Config",
"Blip2QFormerConfig",
"Blip2VisionCon... | 301 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
fr... | 681 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
def ... | 681 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPanoramaPipeline,
... | 709 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''google/umt5-small''': '''https://huggingface.co/google/umt5-small/resol... | 144 | 0 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@require_torch
@re... | 148 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : Tuple = ["image_processor", "tokenizer"]
__A : Any = "... | 340 | 0 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _A ( __magic_name__ ):
lowercase__ ... | 611 |
_snake_case = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _A ( __magic_name_... | 611 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase__ : List[Any] = {'configuration_vit': ['VIT_PRETRAINED_CONFIG_ARCHIVE_MAP... | 31 |
'''simple docstring'''
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tes... | 131 | 0 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
SCREAMING_SNAKE_CASE__ = Lock()
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[Any] , lowerCamelCase_ : List[Any] , lowerCamelCase_... | 700 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''facebook... | 577 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
_lowerCAmelCase = ['small', 'medium', 'large']
_lowerCAmelCase = 'lm_head.decoder.weight'
_lowerCAmelCase = 'lm_head.weight'
def UpperCamelCase ( _A ... | 264 |
"""simple docstring"""
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def UpperCamelCase ( _A = "laptop" ) -> DataFrame:
lowercase : List[str] = F"""https://www.amazon.in/laptop/s?k={product}"""
low... | 264 | 1 |
import torch
from torch import nn
class lowerCamelCase ( nn.Module ):
'''simple docstring'''
def __init__( self , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase=1 , lowerCAmelCase=False ):
... | 709 |
def snake_case__ ( __SCREAMING_SNAKE_CASE ) -> int:
UpperCAmelCase_ = [1]
UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ = 0, 0, 0
UpperCAmelCase_ = ugly_nums[ia] * 2
UpperCAmelCase_ = ugly_nums[ia] * 3
UpperCAmelCase_ = ugly_nums[i... | 23 | 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
_lowerCamelCase : List[str] = logging.get_logger(__name__)
_lowerCamelCase ... | 352 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mas... | 352 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : Optional[Any] = logging.get_logger(__name__)
_a : Dict = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
# See all ... | 710 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerFo... | 87 | 0 |
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