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 |
|---|---|---|---|---|
"""simple docstring"""
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... | 237 |
"""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
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_S... | 237 | 1 |
from __future__ import annotations
from typing import Any
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self , __lowerCamelCase ) -> Tuple:
_SCREAMING_SNAKE_CASE : Tuple = num_of_nodes
_SCREAMING_SN... | 704 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'
),
# See a... | 381 | 0 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def _A ( SCREAMING_SNAKE_CASE = "" ):
UpperCAmelCase__: Optional[Any] = url or "https://www.imdb.com/chart/top/?ref_=nv_mv_250"
UpperCAmelCase__: str = BeautifulSoup(requests.get(__lowerCAme... | 113 |
import numpy as np
def __lowercase ( __lowerCAmelCase : np.ndarray , __lowerCAmelCase : float ):
return np.where(vector > 0 , __lowerCAmelCase , (alpha * (np.exp(__lowerCAmelCase ) - 1)) )
if __name__ == "__main__":
import doctest
doct... | 335 | 0 |
class __UpperCamelCase :
"""simple docstring"""
def __init__( self : Optional[Any] , _A : Dict , _A : Optional[int] ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : str = name
__SCREAMING_SNAKE_CAS... | 131 |
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
lowercase_ = logging.get_logger(__name__)
def a__ ( snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Opt... | 131 | 1 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def __UpperCAmelCase ( __... | 14 |
"""simple docstring"""
import itertools
import math
def lowerCamelCase ( _UpperCamelCase : 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:
... | 139 | 0 |
from __future__ import annotations
def UpperCamelCase__( UpperCamelCase__ : list[list[int]] )->int:
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
... | 212 |
# 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... | 212 | 1 |
import math
__A : List[str] = 10
__A : Any = 7
__A : str = BALLS_PER_COLOUR * NUM_COLOURS
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE = 20 ) -> str:
"""simple docstring"""
_A = math.c... | 27 | UpperCamelCase = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
UpperCamelCase ... | 520 | 0 |
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_... | 713 |
# 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 requir... | 94 | 0 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
lowerCAmelCase_ : List[str] = 6378137.0
lowerCAmelCase_ : Dict = 6356752.314245
lowerCAmelCase_ : List[Any] = 6378137
def _lowerCamelCase (__lowerCamelCase : List[str] , ... | 489 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils i... | 530 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
_... | 574 |
'''simple docstring'''
from pathlib import Path
import fire
def __UpperCAmelCase ( UpperCamelCase__ :str , UpperCamelCase__ :str , UpperCamelCase__ :int ) -> List[Any]:
snake_case__ : int = Path(UpperCamelCase__ )
snake_... | 574 | 1 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
UpperCAmelCase__ = logging.getLogger(__name__)
@dataclass
class a ( lowerCAmelCase_ ):
_snake_ca... | 277 | """simple docstring"""
from collections.abc import Generator
def __UpperCAmelCase ( ):
"""simple docstring"""
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def __UpperCAmelCase... | 277 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = {'vocab_file': 'vocab.json'}
__SCREAMING_SNAKE_CASE = {
... | 713 |
'''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, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
... | 340 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIVE_MA... | 45 | import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case ( __snake_case ):
"""simple docstring"""
__lowerCAmelCase = (UnCLIPScheduler,)
def snake_case__ ( self , **lowerCAmelCase_ ):
__lower... | 321 | 0 |
'''simple docstring'''
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 imp... | 713 |
'''simple docstring'''
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 __snake_case ( __SCREAMING_SNAKE_CASE ):
... | 419 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemak... | 24 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 325 | 0 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase = 10**-10 ):
_UpperCAmelCase : List[str] ... | 40 |
'''simple docstring'''
import os
def __lowerCAmelCase ():
_UpperCAmelCase : List[Any] = os.path.join(os.path.dirname(__lowerCAmelCase ) , "num.txt" )
with open(__lowerCAmelCase ) as file_hand:
return str(sum(int(__lowerCAmelCase ) for line in file_hand... | 40 | 1 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
ren... | 685 |
'''simple docstring'''
import math
def __UpperCAmelCase (lowercase__ ) -> 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, ... | 685 | 1 |
'''simple docstring'''
import inspect
import unittest
class _a ( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase_ ( self ):
'''simple docstring'''
t... | 508 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepi... | 508 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class SCREAMING_... | 169 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowercase ... | 169 | 1 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"vocab_file": "vocab.json",
"merges_file": "merges.txt",
}
lowercase... | 711 | import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...test_config... | 390 | 0 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_avai... | 555 | def lowercase( UpperCamelCase_ , UpperCamelCase_ ) -> List[str]:
'''simple docstring'''
_enforce_args(UpperCamelCase_ , UpperCamelCase_ )
if n == 0:
return 0
UpperCamelCase = float("""-inf""" )
for i in range(1 , n + 1 ):
UpperCamelCase ... | 537 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( lowerCAmelCase__ :float , lowerCAmelCase__ :float , lowerCAmelCase__ :float , ) -> tuple:
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0 )... | 197 | """simple docstring"""
def UpperCAmelCase__ ( lowerCAmelCase__ :str , lowerCAmelCase__ :int ) -> list:
'''simple docstring'''
lowercase = word.split()
def justify(lowerCAmelCase__ :list , lowerCAmelCase__ :int , lowerCAmelCase__ ... | 197 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _SCREAMING_SNAKE_CASE ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = ["""image_processor""", """tokenizer"""]
lowercase_ = """ViT... | 59 |
'''simple docstring'''
from __future__ import annotations
def a_ ( __UpperCAmelCase ) -> list[int]:
"""simple docstring"""
snake_case: Tuple =[True] * limit
snake_case: Optional[int] =False
snake_case: U... | 350 | 0 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class SCREAMING_SNAKE_CASE ( snake_c... | 62 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class SCREAMING_SNAKE_CASE ( nn.Module ):
"""simple docstring"""
A_ = 42
A_ = jnp.floataa
def __A ( self: Tuple ) -> Tuple:
_A = nn.Conv(
... | 62 | 1 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def a__ ( _SCREAMING_SNAKE_CASE : Optional[Any] , _SCREAMING_SNAKE_CASE : int=False ) -> List[str]:
"""simple docstring""... | 71 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
__lowerCamelCase : str = WebClient(token=os.environ["""CI_SLACK_BOT_TOKEN"""])
def ... | 501 | 0 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_lowerCAmelCase = logging.getLogger(__name__)
class __A ( a ):
"""simple d... | 717 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class __A ( a ):
"""simple docstring"""
A_ = ''
A_ ... | 318 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
re... | 680 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , ) -> list[float]:
SCREAMING_S... | 680 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassific... | 713 | import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import C... | 647 | 0 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# sin... | 568 |
import comet # From: unbabel-comet
import torch
import datasets
lowercase : List[Any] = datasets.logging.get_logger(__name__)
lowercase : List[str] = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
... | 568 | 1 |
import math
def lowercase__ ( __A: float ,__A: float ):
'''simple docstring'''
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensity
if angle < 0 or angle ... | 501 |
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, List, Literal, NewType, Opt... | 501 | 1 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
UpperCAmelCase_ : List[Any] = '\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. Fo... | 44 |
def __UpperCamelCase (lowerCAmelCase : list[int] ) -> int:
if not numbers:
return 0
if not isinstance(lowerCAmelCase, (list, tuple) ) or not all(
isinstance(lowerCAmelCase, lowerCAmelCase ) for number in numbers ):
raise ValueError('numbers m... | 699 | 0 |
from __future__ import annotations
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self , __lowercase) -> Tuple:
__UpperCamelCase :List[Any] = TypeError(
'''Matrices must be formed from a list of zero or more lists containing at '''
... | 720 | from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
__lowercase = datasets.load_iris()
__lowercase = np.array(data['''data'''])
__lowercase = np.array(data['''target'''])
__lowercase ... | 452 | 0 |
from typing import Any
def A ( snake_case__ : list , snake_case__ : list , snake_case__ : dict , snake_case__ : dict , snake_case__ : dict , ) -> list:
'''simple docstring'''
_validation(
snake_case__ , snake_case__ , sna... | 313 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCAmelCase__ : List[Any] = 4
UpperCAmelCase__ : Optional[Any] = ... | 313 | 1 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class lowercase_ ( a__ ):
__UpperCAmelCase ... | 706 |
'''simple docstring'''
def _UpperCamelCase ( __A ) -> float:
'''simple docstring'''
if edge <= 0 or not isinstance(__A , __A ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def _... | 223 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class __A ( a ):
"""simple docstring"""
def __init__( self , _lowerCamelCase , _lowerCamelCase )-> List[Any]:
lowerc... | 161 |
'''simple docstring'''
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def SCREAMING_SNAKE_CASE ( a_ : str = "" ):
__a = url or 'https://www.imdb.com/chart/top/?ref_=nv_mv_250'
__a = Beautiful... | 539 | 0 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCAmelCase( unittest.TestCase ):
"""simple docstring"""
def __a ( self ... | 709 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__a : str = argparse.ArgumentParser()
parser.add_argument('''--dump_path''', default=N... | 298 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ , lowercase_ ) -> List[str]:
"""simple docstring"""
if height >= 1:
move_tower(height - 1 , lowercase_ , lowercase_ , lowercase_ )
m... | 87 |
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
_lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : ... | 87 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_xlm_roberta''': [
... | 144 |
def _a ( lowerCamelCase__ ) -> int:
lowerCamelCase_ : List[Any] = []
lowerCamelCase_ : int = set({'(', '[', '{'} )
lowerCamelCase_ : Optional[Any] = set({')', ']', '}'} )
lowerCamelCase_ : Dict = ... | 144 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def lowerCAmelCase_ ( SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__ = False ) -> float:
if not arr:
return 0
a_ : Dict = 0 if allow_empty_subarrays else float("-inf" )
a_ : Dict = 0.0
for... | 237 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE_ = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenization_ctrl... | 237 | 1 |
"""simple docstring"""
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedD... | 263 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ : Dict = logging.get_logger(__name__)
a_ : List[Any] = {
'''vocab_file''': '''vocab.json''... | 263 | 1 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.au... | 468 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
A = logging.get_logger(__name__)
def __SCREAMING_SNAKE_CASE ( lowerCamelC... | 449 | 0 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : Optional[int] = "Speech2TextFeatureExtractor"
lowerCamelCase__ : Any = "Speech2TextT... | 645 | """simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 645 | 1 |
'''simple docstring'''
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
fr... | 72 |
from math import sqrt
def snake_case_ ( _SCREAMING_SNAKE_CASE ):
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 are not primes
return False
# All primes number are in format o... | 402 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 706 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__vers... | 688 | 0 |
"""simple docstring"""
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 ...tes... | 76 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
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 impor... | 336 | 0 |
import os
import numpy
import onnx
def _snake_case (_snake_case : Optional[Any] , _snake_case : Optional[int]) -> Tuple:
_lowercase =a.name
_lowercase =b.name
_lowercase =''
_lowercase =''
_lowercase =a =... | 557 |
import os
def _snake_case (_snake_case : Optional[Any]) -> int:
_lowercase =len(grid[0])
_lowercase =len(_snake_case)
_lowercase =0
_lowercase =0
_lowercase =0
# Check vertically, horizontally, diagonally at the same ti... | 557 | 1 |
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 ... im... | 45 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
lowerCAmelCase : Tuple = r"""
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig... | 444 | 0 |
"""simple docstring"""
import os
def UpperCamelCase_ ( SCREAMING_SNAKE_CASE_ = "input.txt" ):
with open(os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE_ ), SCREAMING_SNAKE_CASE_ ) ) as input_file:
SCREAMING_SNAKE_CASE = [
[int(SCREAMING_S... | 704 |
"""simple docstring"""
import os
import sys
import unittest
snake_case = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get... | 406 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE :List[str] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pa... | 628 |
from __future__ import annotations
from collections import Counter
from random import random
class lowerCAmelCase_ :
"""simple docstring"""
def __init__( self ) -> List[str]:
__UpperCamelCase = {}
def __lowercase( self , _SCREAMING_SNAKE_CASE ) ->... | 383 | 0 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE_ = loggi... | 370 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transform... | 370 | 1 |
"""simple docstring"""
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
__magic_name__ = logging... | 129 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSav... | 281 | 0 |
import os
A__ : List[str] = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 1_00, 'D': 5_00, 'M': 10_00}
def a ( lowerCamelCase_ ):
'''simple docstring'''
lowercase__ = 0
lowercase__ = 0
while index < len(lowerCamelCase_ ) - 1:
... | 708 |
class _UpperCAmelCase :
"""simple docstring"""
def __init__( self : Optional[int], lowerCamelCase : Union[str, Any] ):
'''simple docstring'''
# we need a list not a string, so do something to change the type
lowercase__ = arr.split('''... | 671 | 0 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> str:
'''simple docstring'''
snake_case : Tuple = [0 for i in range(r + 1 )]
# nc0 = 1
snake_case : Optional[int] = 1
for i in r... | 638 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 1 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _A ( __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__=1024 ):
lowercase__ , lowercase__ = [], []
lowercas... | 611 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, ... | 611 | 1 |
import os
def UpperCamelCase_( ):
"""simple docstring"""
_lowerCAmelCase :str = os.path.join(os.path.dirname(__magic_name__ ) , 'num.txt' )
with open(__magic_name__ ) as file_hand:
return str(sum(int(__magic_name__ ... | 687 |
from __future__ import annotations
from collections.abc import MutableSequence
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self: List[Any] , _UpperCAmelCase: int , _UpperCAmelCase: MutableSequence[float] ):
if len(_UpperCAmelCase ) != degree... | 687 | 1 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCamelCase__ ( _A ):
"""simple docstring"""
_UpperCamelCase : Any = 'EncodecFeatureExtractor'
_UpperCamelCase : ... | 717 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMSchedul... | 185 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'configuration_clap': [
'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
'ClapAudioConfig',
'ClapConfig',
'ClapTextConfig',
],
'processing_clap': ['... | 25 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCAmelCase = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not is_torch_available():
... | 147 | 0 |
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
A__: Optional[int] = TypeVar('''KT''')
A__: Dict = TypeVar('''VT''')
class _a ( Generic[KT, VT]):
"""simple docstring"""
def __init__( ... | 221 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _a ( unittest.TestCase):
"""simple docstring"""
def UpperCAmelCase_ ( self: Tuple ):
'''simple docstring'''
UpperCamelCase__: Unio... | 221 | 1 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class _UpperCAmelCase ( lowerCAmelCa... | 577 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case: Dict = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 577 | 1 |
def a__ ( snake_case , snake_case ):
"""simple docstring"""
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def a__ ( snake_case , snake_case=0 ):
"""simple docstring"""
return sorted(snake_case , key=lambda snake_case ... | 131 |
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def a__ ( snake_case , snake_case , snake_case , snake_case , snake_case ):
"""simple docstring"""
# load base model
__SCREAMING_SNAKE_CASE : str ... | 131 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
f... | 27 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase__ : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [... | 65 | 0 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class _lowerCame... | 507 |
"""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
_A = """src/transformers"""
# This is to ma... | 507 | 1 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def _UpperCAmelCase ( self , _UpperCAmelCase ) -> Dict:
with open(_UpperC... | 23 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.ut... | 618 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffus... | 700 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffus... | 377 | 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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"""goog... | 122 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
_a: int = """src/diffusers"""
# Matches is_xxx_available()
_a: Tuple = re.compile(r"""is\_([a-z_]*)_available\(... | 162 | 0 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import ... | 717 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 59 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageP... | 24 |
def lowerCAmelCase_ (lowerCAmelCase__: Union[str, Any] , lowerCAmelCase__: Optional[int] ):
"""simple docstring"""
UpperCAmelCase_: List[str] = 0
UpperCAmelCase_: Tuple = len(lowerCAmelCase__ ) - 1
while left <= right:
# avoid d... | 556 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENER... | 710 |
"""simple docstring"""
import numpy as np
def _snake_case ( lowercase__ : np.ndarray ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _snake_case ( lowercase__ : np.ndarray ) -> np.ndarray... | 256 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config ... | 49 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowercase : Union[str, Any] = logging.get_logger(__name__)
lowercase : Optional[int] = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/bl... | 327 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
_lowercase = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"
" Distillation"
)
... | 526 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileViTConfig", "MobileViTOnnxC... | 526 | 1 |
'''simple docstring'''
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_... | 502 |
'''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_pipeli... | 502 | 1 |
'''simple docstring'''
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... | 640 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Any = False
while is_sorted is False: # Until all the indices are traversed keep looping
lowercase_ : List[str] = True
for i in ran... | 640 | 1 |
'''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 _snake_case ( ):
"""simple docstring"""
print("""Making key files...""" )
make_key_f... | 577 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate... | 577 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
_A : str = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
_A : str = ... | 189 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_objects imp... | 189 | 1 |
import argparse
import copy
def _UpperCamelCase ( lowercase__ ):
__SCREAMING_SNAKE_CASE : Tuple = {}
with open(lowercase__ ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
__SCREAMING_SNAKE_CASE : Optional... | 696 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowerCAmelCase_ ( lowerCamelCase ):
# A local function to see if a dot lands in the circle.
def is_in_circle(lowerCamelCase , lowerCamelCase ) -> bool:... | 21 | 0 |
"""simple docstring"""
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""" , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("""input_in_memory_max_size""" , ["""default""", 0, 100 * 2**20, 900 *... | 702 | """simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def UpperCamelCase ( _lowerCAmelCase : str , _lowerCAmelCase : str , _lowerCAmelCase : Optional[str] = None ... | 173 | 0 |
"""simple docstring"""
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCH... | 77 |
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self , __UpperCAmelCase ):
"""simple docstring"""
a__ : Union[str, Any] = data
a__ : Tuple = None
... | 191 | 0 |
lowerCamelCase_ = [
'''Audio''',
'''Array2D''',
'''Array3D''',
'''Array4D''',
'''Array5D''',
'''ClassLabel''',
'''Features''',
'''Sequence''',
'''Value''',
'''Image''',
'''Translation''',
'''TranslationVariableLanguages''',
]
from .audio import Audio
from .... | 161 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json''',
# See all ViT MSN models ... | 161 | 1 |
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ):
"""simple docstring"""
while b:
UpperCAmelCase , UpperCAmelCase = b, a % b
return a
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ):
"""simple docstring"""
r... | 333 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __magic_name__ ( _a):
@staticmethod
@abstractmethod
def _UpperCAmelCase ( __SCREAMING_SNAKE_CASE : ArgumentParser ):
raise NotImplementedError()
@abstractmethod
def _UpperCAmelCase ( self ... | 333 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ : int = logging.get_logger(__name__)
lo... | 156 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 156 | 1 |
'''simple docstring'''
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _UpperCamelCase ( UpperCamelCase__ ):
if not is_accelerate_available():
return method
UpperCAmelC... | 407 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
__A =True
except (ImportError, ModuleNotFoundError):
__A =False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', quiet=True)
def _UpperCamelC... | 407 | 1 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
# Initialise PyTor... | 530 |
from math import factorial
def SCREAMING_SNAKE_CASE__ ( __lowerCAmelCase = 100 ):
return sum(int(__lowerCAmelCase ) for x in str(factorial(__lowerCAmelCase ) ) )
if __name__ == "__main__":
print(solution(int(input('''Enter the Number: ''').strip())))
| 530 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A__ : Optional[Any] = {'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}
try:
... | 153 |
"""simple docstring"""
import math
def lowercase ( __UpperCamelCase = 100 ) -> int:
__magic_name__ = sum(i * i for i in range(1 , n + 1 ) )
__magic_name__ = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return square_of_sum - sum_of_squares
if __name__ == "_... | 490 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase : List[Any] = {
"configuration_deberta": ["DEBERTA_PR... | 720 | """simple docstring"""
import qiskit
def SCREAMING_SNAKE_CASE ( snake_case, snake_case):
__snake_case = qiskit.Aer.get_backend('''aer_simulator''')
# Create a Quantum Circuit acting on the q register
__snake_case = qiskit.QuantumCircuit(snake_cas... | 93 | 0 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forwar... | 32 |
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 ( A__ ):
__A : Dict ... | 32 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _snake_case (__SCREAMING_SNAKE_CASE , unittest.TestCase):
__A : Dict ... | 323 |
'''simple docstring'''
import csv
import tweepy
# Twitter API credentials
_lowerCamelCase = """"""
_lowerCamelCase = """"""
_lowerCamelCase = """"""
_lowerCamelCase = """"""
def a__ ( _SCREAMING_SNAKE_CASE : str ) -> None:
""... | 323 | 1 |
def a__ (__lowercase :int ) -> bool:
if p < 2:
raise ValueError('''p should not be less than 2!''' )
elif p == 2:
return True
_A : Any = 4
_A : List[Any] = (1 << p) - 1
for _ in range(p - 2 ):
_A : Optional[Any] ... | 206 |
def a__ (__lowercase :str , __lowercase :str ) -> float:
def get_matched_characters(__lowercase :str , __lowercase :str ) -> str:
_A : Union[str, Any] = []
_A : Dict = min(len(_stra ) , len(_stra ) ) // 2
... | 206 | 1 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def _lowerCAmelCase ( s... | 702 |
"""simple docstring"""
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ... | 66 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( SCREAMING_SNAKE_CASE_ : Union[st... | 421 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTConfig", "DeiTOnnxConfig... | 586 | 0 |
"""simple docstring"""
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_... | 36 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def __magic_name__ ( lowercase ):
if "cls_token" in name:
SCREAMING_SNAKE_CASE_: Optional[int] ... | 36 | 1 |
"""simple docstring"""
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_... | 58 |
'''simple docstring'''
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
f... | 467 | 0 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE: int ):
"""simple docstring"""
if num < 0:
return False
_lowerCAmelCase = num
_lowerCAmelCase = 0
while num > 0:
_lowerCAmelCase = r... | 491 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
_snake_case = logging.get... | 491 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pow, sqrt
def snake_case_ ( __snake_case : float , __snake_case : float , __snake_case : float) -> dict[str, float]:
if (resistance, reactance, impedance).count(0) != 1:
raise V... | 274 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def UpperCAmelCase_ ( ) -> Optional[Any]:
'''simple docstring'''
A_ = HfArgumentParser(_UpperCAmelCase )
A_ = parser.parse_args_into_dataclasses()[0]
A... | 188 | 0 |
class lowercase :
def __init__( self , A_ ) -> List[str]:
"""simple docstring"""
# we need a list not a string, so do something to change the type
UpperCamelCase = arr.split(',' )
def __UpperCamelCase ( self ) -> int:
"""simple docstring"... | 3 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_camembert impor... | 3 | 1 |
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, List, Literal, ... | 136 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before toke... | 136 | 1 |
"""simple docstring"""
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGE... | 509 |
"""simple docstring"""
# coding=utf-8
# Copyright 2023 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
#... | 509 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 115 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_c... | 115 | 1 |
'''simple docstring'''
import requests
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> None:
'''simple docstring'''
snake_case_ = {'''Content-Type''': '''application/json'''}
snake_case_ = requests.post(SCREAMING_SNAKE_CASE_, json={'''text'''... | 700 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from... | 593 | 0 |
from __future__ import annotations
def a_ ( lowerCAmelCase_ : list[float] ):
if len(lowerCAmelCase_ ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
if any(i <= 0 for i in nums ):
raise ValueError('All values must be g... | 53 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : List[str] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : List[str] = {
'Salesforce/blip-vqa-base': 'https://huggingfa... | 311 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def snake_case_ (__A : dict , __A : str , __A : set , __A : set , __A : dict , __A : dict , __A : PriorityQueue , __A : dict , __A : ... | 218 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs... | 218 | 1 |
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