code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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
#... | 75 |
"""simple docstring"""
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __magic_name__ ( __snake_case : Optional[Any] , __snake_case : ... | 202 | 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 ... | 75 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__A = R'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the model outputs. Read the documenta... | 75 | 1 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
a_ = logging.getLogger()
@unittest.skip('Temporarily disable the doc tests.' )
@require_torch
@... | 76 |
from typing import Any
class __SCREAMING_SNAKE_CASE :
def __init__( self : List[Any] , A : Any ) ->Optional[int]:
lowerCamelCase__ : Optional[int] = data
lowerCamelCase__ : Any = None
class __SCREAMING_SNAK... | 142 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
a = logging.get_logger(__name__)
def _snake_case ( _snake_case : Union[tf.Tensor, np.ndarray] ) -> List[int]:
'''simple d... | 271 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
a = [8, 5, 9, 7]
a = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
a = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, 1, 0, 5],
[1, ... | 271 | 1 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowerCAmelCase_ = {
# 1536-bit
5: {
'''prime''': int(
... | 8 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from tr... | 104 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device... | 367 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : List[Any] = {
"junnyu/roformer_chin... | 41 | 0 |
'''simple docstring'''
def _UpperCamelCase ( __A ) -> list:
'''simple docstring'''
UpperCamelCase__ = len(__A )
for i in range(1 , __A ):
UpperCamelCase__ = collection[i]
UpperCamelCase__ = 0
... | 80 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
a_ :Optional[Any] = {"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerConf... | 277 | 0 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class A :
"""simple docstring"""
lowerCamelCase = None
lowerCamelCase = False
lowerCamelCase = F... | 282 |
import unittest
from transformers import LiltConfig, 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_modeling_common import ModelTesterMi... | 282 | 1 |
'''simple docstring'''
def a_ ( __snake_case : list ) -> bool:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
if len(__sna... | 75 |
'''simple docstring'''
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
... | 75 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Union[str, Any] = logging.get_logger(__name__)
_snake_case : Dict = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class _UpperCAmelC... | 360 |
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
_snake_case : Union[str, Any] = False
try:
_snake_case ... | 207 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCAmelCase = {
"""configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfi... | 271 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__lowerCAmelCase = TypeVar("""T""")
class UpperCAmelCase__ ( Generic[T] ):
"""simple docstring"""
def __init__( self : Tuple ,_a :... | 271 | 1 |
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
return int((input_a, input_a).count(1 ) != 0 )
def snake_case_ ( ):
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
assert or_gate(1 , 0 ) == 1
ass... | 306 |
def snake_case_ ( lowerCAmelCase_ : int = 200 ):
__lowercase : List[str] = [1, 2, 5, 10, 20, 50, 100, 200]
__lowercase : List[str] = [0] * (pence + 1)
__lowercase : Optional[Any] = 1 # base case: 1 way to make 0 pence
... | 306 | 1 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class _SCREAMING_SNAKE_CASE ( _a ):
def __init__( self : str , __lowerCamel... | 38 |
'''simple docstring'''
from __future__ import annotations
import requests
_A : str =set(
'''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post catego... | 41 | 0 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.nn as nn
... | 71 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
_lowercase: Optional[Any] = "\\n@misc{chen2021evaluating,\n title={Evaluating Large ... | 71 | 1 |
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_utils import OnnxRuntimeModel
... | 282 |
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
_lowerCamelCase : List[str] = logging.get... | 282 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils im... | 136 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCamelCase :
'''simple docstring'''
def __init__( self : List[str] , lowerCAmelCase_ : int ) -> None:
'''simple docstring'''
A__ : Any =num... | 136 | 1 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ... | 5 |
from math import asin, atan, cos, radians, sin, sqrt, tan
A__ : Optional[int] = 637_8137.0
A__ : List[str] = 635_6752.31_4245
A__ : Union[str, Any] = 6_37_81_37
def a ( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ ):
'''simple do... | 207 | 0 |
from __future__ import annotations
def UpperCamelCase ( _A ):
"""simple docstring"""
if len(_A ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
raise ValueError("""All... | 138 |
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,... | 138 | 1 |
def __lowerCamelCase ( snake_case__ ,snake_case__ ) -> float:
"""simple docstring"""
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0:
raise ValueError("""Impossible bulk mo... | 306 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __UpperCAmelCase :
def __init__( self: List[str] , UpperCAmelCase_: Dict ):
'''simple docstring'''
_SCREAMING_SNAKE_CASE ... | 306 | 1 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
fro... | 79 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
a : Any = {'''configuration_fnet''': ['''FNET... | 79 | 1 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
... | 71 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
A_ :List[str] = '''\
@misc{chen2021evaluating,
title={Ev... | 71 | 1 |
def lowerCAmelCase_ ( _snake_case : list ) -> float:
'''simple docstring'''
__magic_name__ : Any = 0
while len(_snake_case ) > 1:
__magic_name__ : List[Any] = 0
# Consider two files with minimum cost to be merged
for _ in range(2 ):
... | 41 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
MusicgenProcessor,
... | 41 | 1 |
"""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... | 136 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> list:
'''simple docstring'''
lowercase_ = len(__lowerCAmelCase )
lowercase_ = [[0] * n for i in range(__lowerCAme... | 136 | 1 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmb... | 9 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
_UpperCAmelCase : List[str] = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the gro... | 9 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusion.modeling_roberta_series import (
... | 138 |
from datetime import datetime as dt
import os
from github import Github
__A : Dict = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def SCREAMING_SNAKE_CASE__ ( ) -> int... | 138 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case : Optional[Any] = logging.get_logger(__name__)
_snake_case ... | 179 |
'''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from d... | 179 | 1 |
'''simple docstring'''
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDi... | 79 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.json''',
# S... | 79 | 1 |
"""simple docstring"""
import re
def UpperCAmelCase ( UpperCamelCase__ ):
"""simple docstring"""
A__ = re.compile(
r'^(?:0|94|\+94|0{2}94)' r'7(0|1|2|4|5|6|7|8)' r'(-| |)' r'\d{7}$' )
return bool(re.search(UpperC... | 154 | """simple docstring"""
def UpperCAmelCase ( UpperCamelCase__ = 100 ):
"""simple docstring"""
A__ = (n * (n + 1) // 2) ** 2
A__ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main_... | 154 | 1 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def SCREAMING_SNAKE_CASE_ (UpperCamelCase , UpperCamelCase , UpperCamelCase ) -> list[int]:
lowerCamelCase__ : Any = [0] * no_of_pro... | 41 |
'''simple docstring'''
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
... | 41 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class UpperCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
snake_case... | 124 |
import argparse
from collections import defaultdict
import yaml
SCREAMING_SNAKE_CASE :str = 'docs/source/en/_toctree.yml'
def UpperCAmelCase ( a_ ) -> int:
"""simple docstring"""
__A = defaultdict(a_ )
for doc in model_doc:
... | 124 | 1 |
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
@maybe_allow_in_graph
class ... | 9 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipeline_test,
nes... | 9 | 1 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> float:
'''simple docstring'''
_UpperCAmelCase : Dict = (num_of_terms / 2) * (... | 371 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE__ : List[str] ) -> str:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase : Dict = [], []
while len(SCREAMING_SNAKE_CASE__ ) > 1:
_UpperCAmelCase , _Up... | 202 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 179 |
"""simple docstring"""
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, ... | 179 | 1 |
import numpy as np
def _SCREAMING_SNAKE_CASE ( lowercase : np.ndarray ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _SCREAMING_SNAKE_CASE ( lowercase : np.ndarray ):
'''simple docstring'''
... | 367 |
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
f... | 208 | 0 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class _SCREAMING_SNAKE_CASE ( lowerCAmelCase__ , lowerCAmelCase__):
_Uppe... | 154 |
def __UpperCamelCase ( _A : Dict ) ->List[str]:
"""simple docstring"""
lowerCamelCase_ =[0] * len(_A )
lowerCamelCase_ =[]
lowerCamelCase_ =[]
lowerCamelCase_ =0
for values in graph.values():
for i in ... | 154 | 1 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def a__ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int , SCREAMIN... | 133 |
"""simple docstring"""
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('''3.8'''):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata... | 133 | 1 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> list[list[float]]:
snake_case : Optional[Any] = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implem... | 124 |
import math
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> int:
if not isinstance(lowercase ,lowercase ):
snake_case : List[Any] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(lowercase )
if number < 1:
snake... | 124 | 1 |
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... | 59 |
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that ... | 59 | 1 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
_UpperCamelCase : Tuple = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. a... | 304 |
"""simple docstring"""
from __future__ import annotations
from functools import lru_cache
from math import ceil
_A : Optional[Any] = 1_00
_A : Optional[int] = set(range(3, NUM_PRIMES, 2))
primes.add(2)
_A : int
for prime in range(3, ceil(NUM_PRIMES**... | 202 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''xlm-... | 334 |
'''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/f... | 334 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCAmelCase = {
'''configuration_efficientformer''': [
... | 298 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def a_ ( *_lowerCAmelCase ,_lowerCAmelCase = None ,_lowerCAmelCase=True ,_lowerCAmelCase=2 ) -> List[str]:
fr... | 208 | 0 |
"""simple docstring"""
def lowerCAmelCase (__UpperCamelCase : str ):
"""simple docstring"""
if n_term == "":
return []
__UpperCamelCase =[]
for temp in range(int(snake_case__ ) ):
series.append(F"""1/{temp + 1}""" if series else '''1''' )
retu... | 365 | """simple docstring"""
import os
from pathlib import Path
def lowerCAmelCase ():
"""simple docstring"""
from torch.utils.cpp_extension import load
__UpperCamelCase =Path(__UpperCamelCase ).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
__Uppe... | 85 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __lowerCAmelCase ( ... | 133 |
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 GPTaTokenizer
if TYPE_CHECKIN... | 133 | 1 |
'''simple docstring'''
import numpy as np
def lowercase_ ( __A , __A , __A , __A , __A ) -> Union[str, Any]:
_snake_case = int(np.ceil((x_end - xa) / h ) )
_snake_case = np.zeros((n + 1,) )
_snake_case ... | 368 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from typing import Any
class __UpperCAmelCase :
def __init__( self ):
"""simple docstring"""
_snake_case = []
_snake_case = 0
_snake_case... | 160 | 0 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = R"""
Args:
input_ids (`torch.L... | 59 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def UpperCamelCase ( __lowerCamelCase : Dataset , __lowerCamelCase : Dict[str, str] ):
... | 59 | 1 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
_A : int = '__DUMMY_TRANSFORMERS_USER__'
_A : List[Any] = 'Dummy User'
_A : Optional[Any] = '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'
_... | 353 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Any = logging.get_logger(__name__)
_A : int = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase... | 265 | 0 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_lowerCamelCase =logging.get_logger(__name__)
_lowerCamelCase ={"vocab_file": "vocab.json", "merges_file... | 334 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenizer,... | 334 | 1 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
UpperCAmelCase : Any = logging.getLogger(__name__)
class lowerCAmelCase__ ( __lowercase )... | 361 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
# TODO: upload to AWS
UpperCAmelCase : Optional[int] = {
'yjernite/retribert-base-uncased': (
'https... | 331 | 0 |
'''simple docstring'''
def __lowercase ( __lowercase ) -> bool:
'''simple docstring'''
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 79 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def UpperCamelCase_( snake_case : Callable ):
'''simple docstring'''
@wraps(snake_case )
def _inner_fn(*snake_case : Optional[int] , **snak... | 85 | 0 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def _lowercase ( _UpperCAmelCase , _UpperCAmelCase = "cpu" , _UpperCAmelCase = None ) -> None:
lowerCamelCase =torch.load(_UpperCAmelCase , map_location=_UpperCAmelCase )
... | 352 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCAmelCase__ : Optional[Any] ={
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pyt... | 262 | 0 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : Tuple = logging.get_logger(__name__)
A__ : Optional[Any] = {
'''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/config.json''',
'''xlnet-large-cas... | 103 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_ima... | 160 | 0 |
'''simple docstring'''
import inspect
import re
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_config_docstrings.py
UpperCamelCase : Union[str, Any] = ... | 360 | '''simple docstring'''
import unittest
from transformers import XLMConfig, 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_modeling_common impo... | 345 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigT... | 133 |
'''simple docstring'''
from itertools import count
def __lowerCamelCase ( _lowercase = 5_0 ) -> int:
UpperCAmelCase : Any = [1] * min_block_length
for n in count(_lowercase ):
fill_count_functions.append(1 )
for block_length in... | 265 | 0 |
from __future__ import annotations
from fractions import Fraction
def __UpperCAmelCase ( UpperCAmelCase_ : Any , UpperCAmelCase_ : Dict ) -> bool:
'''simple docstring'''
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / ... | 361 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_d... | 95 | 0 |
'''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
lowerCamelCase : Any = logging.get_logger(__name__)
lowerCamelCase : D... | 47 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 331 | 0 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase = 0, __lowerCamelCase = 0 ):
_SCREAMING_SNAKE_CASE : Any = right or len(__lowerCamelCase ) - 1
if left > right:
return -1
elif list_data[left] == key:
retu... | 354 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase__ =logging.get_logger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def __init__( self , *__lowerCamelCase ... | 325 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __A ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , )-> float | int:
... | 39 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import to... | 262 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(check_d... | 211 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = OrderedDict(
[
... | 211 | 1 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
__A = logging.get_logger(__name__)
def lowerCAmelCase_ ( __a ) -> int:
"""simple docstring"""
lowerCamelCase... | 10 |
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=__snake_case ):
'''simple docstring'''
A__ : Tuple = ["flax"]
def __init__( self: str ,*lowerCamelCase_: int ,**lowerCamelCase_: List[str] ) -> str:
requires... | 345 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'''goo... | 355 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a__ ( unittest.TestCase ):
@prop... | 102 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def a_ ( lowerCamelCase , lowerCamelCase ):
if len(lowerCamelCase ) != 2 or len(a[0] ) != 2 or len(lowerCamelCase ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' ... | 98 |
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __lowerCAmelCase :
pass
| 95 | 0 |
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'The `image_to_image.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionImg2ImgPipeline` instead.'
)
| 361 |
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE... | 194 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Tuple = logging.get_logger(__name__)
__lowerCamelCase : str = {
'''microsoft/git-base''': '''https://huggingface.co/microsoft/git-base/resolve/... | 18 |
import collections
import importlib.util
import os
import re
from pathlib import Path
SCREAMING_SNAKE_CASE__ = """src/transformers"""
# Matches is_xxx_available()
SCREAMING_SNAKE_CASE__ = re.compile(r"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
SCREAMING_SNAKE_CASE... | 325 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ = {
'''configuration_efficientformer''': [
'''EFFICIENTFORMER_PRET... | 175 |
"""simple docstring"""
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
Dist... | 175 | 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
lowercase_ ... | 211 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class __A ( A ):
'''simple docstring'''
__lowerCamelCase : str
__lowerCamelCase : int
def lowerCAmelCase (__A):
"""simple docstring"""
if not isinstance(__A... | 211 | 1 |
"""simple docstring"""
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 _SCREAMING_SNAKE_C... | 239 |
"""simple docstring"""
from __future__ import annotations
import math
def __lowerCamelCase ( a_ : int , a_ : int , a_ : bool , a_ : list[int] , a_ : float ) -> int:
if depth < 0:
raise Va... | 239 | 1 |
"""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
... | 25 |
"""simple docstring"""
import math
def lowercase ( _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 multiples of 3 ar... | 102 | 0 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 358 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
... | 58 | 0 |
from collections import deque
def _A ( SCREAMING_SNAKE_CASE : List[str] ):
"""simple docstring"""
a__ : str =len(SCREAMING_SNAKE_CASE )
a__ : Tuple =deque()
a__ : List[Any] =[False for _ in range(SCREAMING_SNAKE_... | 95 |
"""simple docstring"""
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers impor... | 194 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _lowerCamelCase(__UpperCamelCase = "https://www.worldometers.info/coronavirus" ) -> dict:
_lowerCAmelCase =BeautifulSoup(requests.get(__UpperCamelCase ).text , """html.parser""" )
_lowerCAmelCase =soup.... | 341 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenizati... | 341 | 1 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
a_ = ... | 175 | from __future__ import annotations
def __lowercase ( lowerCamelCase : Optional[Any] , lowerCamelCase : Dict , lowerCamelCase : Union[str, Any] , lowerCamelCase : List[str] ): # noqa: E741
while r - l > 1:
UpperCamelCase_ : Union[str, Any] = (l + r)... | 175 | 1 |
'''simple docstring'''
lowercase__ = 9.8_06_65
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = g ) -> float:
'''simple docstring'''
if fluid_density <= 0:
raise ValueError('''Impossible fluid density''' )
i... | 83 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 83 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : list[int] ) -> int:
if not numbers:
return 0
if not isinstance(UpperCAmelCase__ , (list, tuple) ) or not all(
isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for n... | 239 | '''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn #... | 239 | 1 |
'''simple docstring'''
def a__ ( lowercase : int ) -> bool:
"""simple docstring"""
if p < 2:
raise ValueError('''p should not be less than 2!''' )
elif p == 2:
return True
_UpperCamelCase = 4
_UpperCamelCase = (1 << p) - 1
fo... | 356 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(lowercase, x % y )
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstrin... | 287 | 0 |
"""simple docstring"""
import math
def lowercase (SCREAMING_SNAKE_CASE_ : int ) -> str:
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = 0
while num > 0:
SCREAMING_SNAKE_CASE = num % 8
SCR... | 113 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import... | 58 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __A ( _SCREAMING_SNAKE_CASE ):
"""simple docstring"""
__lowerCAmelCase = "WhisperFeatureExtractor"
__lowerCAmelCase = "WhisperTokenizer"
def __init__( self ... | 363 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
... | 215 | 0 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE = "https://www.worldometers.info/coronavirus" ):
_snake_case = BeautifulSoup(requests.get(_SCREAMING_SNAKE_CASE ).text , """html.parser""" )
... | 341 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, requi... | 341 | 1 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
_UpperCAmelCase : Any = None
try:
import msvcrt
except ImportError:
_UpperCAmelCase : Any = None
try:
import fcntl
except ImportError:... | 9 |
'''simple docstring'''
from __future__ import annotations
import math
def __magic_name__( lowerCamelCase, lowerCamelCase):
if len(lowerCamelCase) != 2 or len(a[0]) != 2 or len(lowerCamelCase) != 2 or len(b[0]) != 2:
raise Exception('''Matrices are not 2x2''')
__lowerC... | 9 | 1 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
snake_case_ : str = '\\n\n'
snake_case_ : str = '\nPerplexity (PPL) is one of the most common m... | 83 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
_UpperCamelCase : List[str] = abs(UpperCAmelCase_ )
_UpperCamelCase : int = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def A__ ( UpperCAmelCase_ ):
... | 83 | 1 |
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_flax_available():
import ... | 131 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load... | 131 | 1 |
'''simple docstring'''
A__ : str = [
"""DownloadConfig""",
"""DownloadManager""",
"""DownloadMode""",
"""StreamingDownloadManager""",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import ... | 185 |
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 287 | 0 |
# Lint as: python3
import itertools
import os
import re
snake_case_ = re.compile(r'''([A-Z]+)([A-Z][a-z])''')
snake_case_ = re.compile(r'''([a-z\d])([A-Z])''')
snake_case_ = re.compile(r'''(?<!_)_(?!_)''')
snake_case_ = re.compile(r'''(_{2,})''')
snake_case_ = r'''^\w+... | 216 |
import math
import sys
def snake_case__ ( SCREAMING_SNAKE_CASE_ : int ):
'''simple docstring'''
if number != int(SCREAMING_SNAKE_CASE_ ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueError('the valu... | 216 | 1 |
__snake_case = {
"""Pillow""": """Pillow""",
"""accelerate""": """accelerate>=0.11.0""",
"""compel""": """compel==0.1.8""",
"""black""": """black~=23.1""",
"""datasets""": """datasets""",
"""filelock""": """filelock""",
"""flax""": """flax>=0.4.1""",
"""hf-doc-builder"... | 259 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.ut... | 215 | 0 |
'''simple docstring'''
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 : Optional[int] = logging.get_logger(__name__)
__A : List[Any]... | 8 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__A : Optional[int] = logging.get_logger(__name__)
class __UpperCamelCase ( lowercase__ ):
def __init__( self :List[str] ,*_Upp... | 8 | 1 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : List[str] =None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] =None
try:
import fcntl
except ImportError:
__lowerCAmelCase : str ... | 9 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _lowercase ( unittes... | 9 | 1 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_co... | 14 |
def lowerCamelCase ( a_ ) -> bool:
lowerCAmelCase_ = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
lowerCAmelCase_ = set()
return any(
node not in visited and depth_first_s... | 14 | 1 |
# Lint as: python3
import itertools
import os
import re
lowerCamelCase = re.compile(R'''([A-Z]+)([A-Z][a-z])''')
lowerCamelCase = re.compile(R'''([a-z\d])([A-Z])''')
lowerCamelCase = re.compile(R'''(?<!_)_(?!_)''')
lowerCamelCase = re.compile(R'''(_{2,})''')
lowerCamelCase ... | 131 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _a ( _lowercase):
_a : Union[str, Any] = ['''image_processor''', '''tokenizer''']
_a : List[Any] = '''ChineseCLIPImageProcess... | 131 | 1 |
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,
WavaVecaFeatureExtractor,
WavaV... | 42 |
import os
def __lowerCamelCase ( __magic_name__ : str = "input.txt" ):
with open(os.path.join(os.path.dirname(__magic_name__ ) , __magic_name__ ) ) as input_file:
a__: str =[
[int(__magic_name__ ) for element in line.split("," )]
... | 42 | 1 |
import random
from typing import Any
def __UpperCamelCase ( lowerCAmelCase__ : list ):
for _ in range(len(lowerCAmelCase__ ) ):
__a : Optional[Any] = random.randint(0 , len(lowerCAmelCase__ ) - 1 )
__a : Union[str, Any] = random.randint(0 , len(lowerCAmelCase__ ) -... | 216 |
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
lowercase__ ={
'E': 12.70,
'T': 9.06,
'A': 8.17,
'O': 7.51,
'I': 6.97,
'N': 6.75,
'S': 6.33,
'H': 6.09,
'R': 5.99,
'D': 4.25,
'L': 4.03,
'C': 2.78,
'U': 2.76,
'M': 2.41,
... | 216 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils im... | 279 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class __lowerCAmelCase ( nn.Module ):
lowerCamelCase_ : int
lowerCamelCase_ : int
lowerCamelCase_ ... | 279 | 1 |
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_ = logging.get_logger(__name__)
lowerCAmelCase_ = '''▁'''
lowerCAm... | 8 |
import math
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(SCREAMING_SNAKE_CASE__ )
else:
if x == 0: ... | 8 | 1 |
"""simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class __a :
'''simple docstring'''
def __init__( self , _a , _a , _a , _a , _a , _a=0.2 , _a=0.2 ) -> Optional[Any]:
"""simple ... | 56 |
"""simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
a :str = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0... | 56 | 1 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common ... | 14 |
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ ) -> List[Any]:
"""simple docstring"""
A__ ... | 14 | 1 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def UpperCAmelCase__ (snake_case__ : int = 8 ):
"""simple docstring"""
_snake_case : List[str] = ascii_letters + ... | 359 |
"""simple docstring"""
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from... | 132 | 0 |
'''simple docstring'''
from __future__ import annotations
class __UpperCAmelCase :
def __init__( self , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case = TypeError(
'Matrices must be formed from a list of zero or more lists ... | 42 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@... | 42 | 1 |
'''simple docstring'''
def _A ( A__ = 1000 ):
"""simple docstring"""
__lowercase , __lowercase = 1, 1
__lowercase = 2
while True:
__lowercase = 0
__lowercase = fa + fa
__lowercase , __lowercase = fa, f
index += 1
for _... | 52 |
'''simple docstring'''
import string
def _A ( A__ ):
"""simple docstring"""
for key in range(len(string.ascii_uppercase ) ):
__lowercase = ''''''
for symbol in message:
if symbol in string.ascii_uppercase:
__lowercase = string.ascii_uppercase.find(A__... | 52 | 1 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from tr... | 279 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __lowerCAmelCase ( _a ):
lowerCamelCase_... | 279 | 1 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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/... | 243 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ : List[Any] = {
'configuration_vision_text_dual_encoder': ['... | 243 | 1 |
'''simple docstring'''
import re
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
snake_case_ = re.compile(
r'''^(?:0|94|\+94|0{2}94)''' r'''7(0|1|2|4|5|6|7|8)''' r'''(-| |)''' r'''\d{7}$''' )
return bool(re.search(__UpperCAmelCase, __U... | 56 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simp... | 56 | 1 |
'''simple docstring'''
import math
from collections.abc import Iterator
from itertools import takewhile
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number ... | 101 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax impo... | 101 | 1 |
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