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 argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentatio... | 545 |
"""simple docstring"""
def A ( __snake_case: int ) -> int:
"""simple docstring"""
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
__magic_name__ = 1
__magic_name__ = 1
while repunit:
... | 545 | 1 |
"""simple docstring"""
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageCla... | 600 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import ... | 600 | 1 |
from __future__ import annotations
def _UpperCamelCase (a__ :Union[str, Any] , a__ :str , a__ :Dict , ):
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supply more or less th... | 619 |
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 imp... | 431 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import Counter
from random import random
class A__ :
"""simple docstring"""
def __init__( self : List[str] ):
a__ : List[str] = {}
def _UpperCamelCase( self : Optional[int] ... | 710 |
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
UpperCamelCase : Optional[Any] = 0
UpperCamelCase : Optional[Any] = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0... | 151 | 0 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDa... | 16 |
'''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 snake_case ( l... | 675 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_big_... | 701 |
import os
from datetime import datetime as dt
from github import Github
A : Union[str, Any] = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def _lowe... | 473 | 0 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
... | 443 |
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
AutoencoderKL,
D... | 302 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase = {'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_M... | 709 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImag... | 190 | 0 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.ut... | 646 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging... | 481 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set... | 720 |
"""simple docstring"""
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
... | 100 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase: str = logging.get_logger(__name__)
_lowercase: List[Any] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'''
... | 192 | import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
_lowercase: str = '''sshleifer/bart-tiny-random'''
_lowercase: ... | 192 | 1 |
"""simple docstring"""
from math import factorial
def lowercase ( lowerCAmelCase__ : int = 100 ) -> int:
return sum(int(lowerCAmelCase__ ) for x in str(factorial(lowerCAmelCase__ ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the Number: ")... | 65 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
lowercase_ = logging.get_logger(__name__)
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self , _a=Non... | 65 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase_ = {
"configuration_efficientformer": [
"EFFICIENTFORMER_PRETRAINED_C... | 470 | """simple docstring"""
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" ,[
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""": 10, """max_num_jobs""":... | 277 | 0 |
'''simple docstring'''
from __future__ import annotations
def __lowercase (_SCREAMING_SNAKE_CASE :float , _SCREAMING_SNAKE_CASE :float , _SCREAMING_SNAKE_CASE :float ):
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('''One and only one a... | 355 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowercase (_SCREAMING_SNAKE_CASE :List[str] , _SCREAMING_SNAKE_CASE :Any , _SCREAMING_SNAKE_CASE :str ):
SCREAMING_SNAKE_CASE : int = 0
if s... | 355 | 1 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
UpperCAmelCase__ : Union[str, Any] = "\\n@inproceedings{snover-etal-2006-study,\n title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",\n author = \"Snove... | 48 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from ... | 143 | 0 |
"""simple docstring"""
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( __lowercase , __lowercase , __lowercase ... | 258 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__magic_name__ = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
try:
... | 258 | 1 |
"""simple docstring"""
# Algorithm for the pigeonhole sorting
def __snake_case ( __A : Union[str, Any] ) -> Optional[int]:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Union[str, Any] = min(__A ) # min() finds the minimum value
SCREAMING... | 265 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
A_ : str = {
'config': [
'EXTERNAL_DATA_FORMAT_SIZE_LIMIT',
'OnnxConfig',
'OnnxConfigWithPast',
'OnnxSeq2SeqConfigWithPast',
'PatchingSpec',
],
'convert': [... | 265 | 1 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
__lowerCAmelCase : Optional[Any... | 714 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def __snake_case ( UpperCamelCase ) -> List[str]:
"""simple docstring"""
return choice(UpperCamelCase )
def __snake_case ( UpperCamelCase , UpperCamelCase ) -> int:
"""s... | 158 | 0 |
'''simple docstring'''
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone... | 185 |
'''simple docstring'''
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def __a ( _UpperCamelCase: str ) -> str:
"""simple docstring"""
return "".join(sorted(_UpperCamelCase ) )
def __a ( ... | 185 | 1 |
import math
import random
def lowercase_ ( _A : float , _A : bool = False ):
"""simple docstring"""
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
A : List[Any] = 0.0_2
def l... | 5 |
import os
def lowercase_ ( _A : str = "input.txt" ):
"""simple docstring"""
with open(os.path.join(os.path.dirname(_A ) , _A ) ) as input_file:
lowerCamelCase__ : List[Any] = [
[int(_A ) for element in line.split("," ... | 5 | 1 |
'''simple docstring'''
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... | 38 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is... | 38 | 1 |
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,
resize,
to_channel_di... | 90 |
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase_ : int):
'''simple docstring'''
lowerCAmelCase__ : Optional[int] = str(lowerCamelCase_)
return len(lowerCamelCase_) == 9 and set(lowerCamelCase_) == set('''123456789''')
def lowerCAmelCase__ (... | 90 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ : List[Any] = {
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
... | 692 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class UpperCamelCase ( lowercase__ ):
'''simple do... | 257 | 0 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
a__: str = logging.getLogger()
... | 212 |
def UpperCamelCase__( UpperCamelCase__ : Optional[int] , UpperCamelCase__ : List[Any] )->List[str]:
A__ = [1]
for i in range(2 , UpperCamelCase__ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k ou... | 212 | 1 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCAmelCase__ ( _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : str = "cpu" , _SCREAMING_SNAKE_CASE : Union[str, None] = None ):
"""simple docstring"""
__a = ... | 225 |
def lowerCAmelCase__ ( _SCREAMING_SNAKE_CASE : list ):
"""simple docstring"""
__a = len(_SCREAMING_SNAKE_CASE )
for _ in range(_SCREAMING_SNAKE_CASE ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
... | 225 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCAmelCase = {
'''configuration_groupvit''': [
'''GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''GroupViTConfig'... | 396 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class _lowerCAmelCase :
def __init__( self : int , a : list[tuple[float, float]] ) -> List[str]:
"""simple docstring"""
lowercase ... | 396 | 1 |
'''simple docstring'''
from __future__ import annotations
_SCREAMING_SNAKE_CASE = list[list[int]]
# assigning initial values to the grid
_SCREAMING_SNAKE_CASE = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
... | 369 |
from __future__ import annotations
import requests
def snake_case_ (__A : str ) -> dict:
__lowerCAmelCase : Tuple = f'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'''
return requests.get(__A ).json()
def snake_case_ ... | 651 | 0 |
"""simple docstring"""
def A__ ( UpperCamelCase ):
if not all(x.isalpha() for x in string ):
raise ValueError("String must only contain alphabetic characters." )
A = sorted(string.lower() )
return len(UpperCamelCase ) == len(set(UpperCamelCase ) )
if __nam... | 524 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_snake_case : str = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies # noqa: E402
# Th... | 524 | 1 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__a :int = '\\n\n'
__a :Any = '\nPerplexity (PPL) is one of the most common metrics for evaluating langua... | 86 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -... | 223 | 0 |
"""simple docstring"""
def _snake_case ( _snake_case : bytes ) -> str:
'''simple docstring'''
return "".join([hex(_snake_case )[2:].zfill(2 ).upper() for byte in list(_snake_case )] )
def _snake_case ( _snake_case : ... | 505 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _snake_case ( _snake_case : List[Any] ) -> Any:
'''simple do... | 505 | 1 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_tor... | 452 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __lowerCAmelCase ( unittest.TestCase , lowercase ):
"""simple docstring"""
def _UpperCAmelCase ( self : List[str] ):
... | 452 | 1 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__A : Dict = logging.get_logger(__name__)
# TODO: upload to AWS
__A : Optional[int] = {
"""yjernite/retribert-base-uncased""": (
"""https://huggingfac... | 716 |
'''simple docstring'''
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import Ten... | 187 | 0 |
from cva import destroyAllWindows, imread, imshow, waitKey
def _lowerCAmelCase ( _lowerCAmelCase ):
'''simple docstring'''
A_ , A_ : Tuple = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for i in range(_lowerCAmelCase ):
for j in... | 569 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.... | 569 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
RandomHorizontalFli... | 235 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Tuple = {
"""configuration_funnel""": ["""FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FunnelConfig"""],
... | 235 | 1 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''huggingface/informer-tourism-monthly''': (
'''https://huggingface.co/hug... | 39 |
class __lowerCamelCase :
"""simple docstring"""
def __init__( self : Union[str, Any] , SCREAMING_SNAKE_CASE__ : int ) -> None:
lowerCAmelCase__ = size
lowerCAmelCase__ = [0] * size
lowerCAmelCase__ = ... | 61 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
UpperCAmelCase = R"""
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model outputs... | 701 |
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is_tf_ava... | 351 | 0 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ ):
def wrapper(*SCREAMING_SNAKE_CASE__ , **SCREAMING_SNAKE_CASE__ ):
sn... | 39 |
"""simple docstring"""
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, requi... | 695 | 0 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common ... | 707 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
r... | 256 | 0 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
RequestCounte... | 62 |
'''simple docstring'''
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs("hub/hopper-medium-v2/unet/hor32", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/unet/hor128", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/value_function", exist_ok=True)
def _UpperCamelC... | 42 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_UpperCAmelCase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase_ ( snake_case__ ):
def __init__( self : List[Any] , ... | 707 |
import pytest
import datasets
# Import fixture modules as plugins
_UpperCAmelCase : Tuple = ["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]
def lowerCAmelCase_ (lowercase__ : Optional[int] , lowercase__ : int ) -> Any:
''... | 288 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, Vi... | 448 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class __SCREAMING_SNAKE_CASE ( _lowerCAmelCase ):
__a =42
__a =42
def __UpperCAmelCase ( SCREAMING_SNAKE_CASE__: str ) -> list[... | 448 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
class _lowerCAmelCase :
"""simple docstring"""
def __init__( self : Any , SCREAMING_SNAKE_CASE : int ) -> None:
"""simple docstring"""
lowerCAmelCase = size... | 702 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def __a ( A__ ) -> Any:
# encoder.embeddings are double copied in ori... | 159 | 0 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoModelWithL... | 401 | import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
B... | 401 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {
'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}
try:
if not is_torch_a... | 299 |
"""simple docstring"""
def lowerCamelCase ( _UpperCamelCase : Dict ) -> Any:
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__UpperCAmelCase : List[str] = len(_UpperCamelCase )
... | 299 | 1 |
'''simple docstring'''
import os
import sys
__UpperCamelCase = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAns... | 26 |
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
SCREAMING_SNAKE_CASE : str = "scheduler_config.json"
class _lowerCamelCase( _a ... | 89 | 0 |
"""simple docstring"""
# 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 wo... | 696 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_comm... | 696 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto im... | 646 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 1 |
from math import ceil
def a__ ( snake_case , snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : str = list(range(0 , SCREAMING_SNAKE_CASE_ ) )
__SCREAMING_SNAKE_CASE : int = [item for sublist in list(device_map.values() ) for item i... | 702 |
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
@require_sentencepiece
@requir... | 131 | 0 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ... | 444 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class A_ ( __lowercase ):
'''simple docstring'''
def __init__( self , *_A ,... | 485 | 0 |
import numpy as np
def lowerCAmelCase ( _lowerCAmelCase : Optional[int] , _lowerCAmelCase : Union[str, Any] ):
"""simple docstring"""
return np.where(vector > 0 , _lowerCAmelCase , (alpha * (np.exp(_lowerCAmelCase ) - 1)) )
if __name__ == "... | 701 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=lowerCAmelCase ):
UpperCAmelCase_ = ["""flax"""]
def __init__( self :List[Any] , *lowerCamelCase :int , **lowerCamelCase :List[Any] ) -> Dict:
requires_backends(s... | 364 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase : Optional[int] = {
'configuration_blend... | 50 |
import numpy as np
def A__ ( _a : np.array ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 385 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def _snake_case ( lowerCamelCase__ : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 244 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase__ ( metaclass=snake_case__ ):
_UpperCAmelCase :Union[str, Any] = ["torch"]
def __init__( self : Optional[Any] , *snake_case__ : Optional[int] , **snake_ca... | 244 | 1 |
from __future__ import annotations
from typing import Any
def lowerCAmelCase__ ( a__ ) ->None:
'''simple docstring'''
create_state_space_tree(a__ , [] , 0 )
def lowerCAmelCase__ ( a__ , a__ , a__ ) ->None:
'''simple docstring'''
if ind... | 547 | from __future__ import annotations
from collections import Counter
from random import random
class _UpperCAmelCase :
'''simple docstring'''
def __init__( self : List[str]) -> Any:
"""simple docstring"""
_UpperCamelCase = {}
def __UpperCAmelCase ( ... | 547 | 1 |
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require_torchaudio
@requir... | 709 |
def _UpperCAmelCase ( a : int = 1000 ):
snake_case__ , snake_case__ = 1, 1
snake_case__ = 2
while True:
snake_case__ = 0
snake_case__ = fa + fa
snake_case__ , snake_case__ = fa, f
index +... | 99 | 0 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig... | 93 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__lowerCamelCase = ""
__lowerCamelCase = ""
__lowerCamelCase = ""
__lowerCamelCase = 1 # (0 is vertical, 1 is horizontal)
def lowercase ( ) -> N... | 490 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoP... | 497 |
"""simple docstring"""
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase_ : List[str] = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",... | 497 | 1 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'datase... | 7 |
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTeacher,
EfficientFormerI... | 148 | 0 |
"""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/LICENS... | 430 |
"""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,
... | 430 | 1 |
"""simple docstring"""
import torch
from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool
if is_datasets_available():
from datasets import load_dataset
class __lowerCAmelCase ... | 695 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 588 | 0 |
'''simple docstring'''
from __future__ import annotations
def __UpperCAmelCase ( UpperCamelCase__ :Union[str, Any] , UpperCamelCase__ :Optional[Any] , UpperCamelCase__ :List[Any] , UpperCamelCase__ :Union[str, Any] , Upper... | 703 |
'''simple docstring'''
import argparse
import os
import re
_lowercase : str ="src/transformers"
# Pattern that looks at the indentation in a line.
_lowercase : List[Any] =re.compile(R"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase : Optional[Any] ... | 574 | 0 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __magic_name__ ( unittest.TestCase ):
"""... | 454 |
import logging
from transformers import PretrainedConfig
_lowerCAmelCase : str = logging.getLogger(__name__)
_lowerCAmelCase : Dict = {
'''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/re... | 454 | 1 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowerCAmelCase_ : Dict = [
# tf -> hf
('/', '.'),
('layer_', 'laye... | 521 |
'''simple docstring'''
import torch
from diffusers import StableDiffusionPipeline
lowerCAmelCase_ : Any = 'path-to-your-trained-model'
lowerCAmelCase_ : Dict = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('cuda')
lowerCAmelCase_ ... | 521 | 1 |
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
a_ : Optional[int] ... | 194 |
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
"""simple docstring"""
@staticmethod
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE ) -> Optional[Any]:
a__ = PartialState()
return not main_process_only or ... | 194 | 1 |
'''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 ...test_modeling_common im... | 435 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class UpperCAmelCas... | 435 | 1 |
from typing import Any
class A__ :
"""simple docstring"""
def __init__( self : Union[str, Any] , lowerCamelCase__ : Any ):
a__ : List[str] = data
a__ : List[Any] = None
def __repr__( self : Tuple ):
return f'''Node({self.data})'''
... | 37 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.set_verbosity... | 408 | 0 |
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ) -> int:
'''simple docstring'''
if len(__snake_case ) != len(__snake_case ):
raise ValueError('''The length of profit and weight must be same.''' )
if max_weight <= 0:
raise ValueError('''max_weight... | 29 |
from math import sqrt
def lowerCAmelCase__(__snake_case ) -> bool:
'''simple docstring'''
assert isinstance(__snake_case ,__snake_case ) and (
number >= 0
), "'number' must been an int and positive"
lowerCamelCase__ = True
# 0 and 1 are none primes.
... | 29 | 1 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import A... | 30 |
from __future__ import annotations
def A__ ( SCREAMING_SNAKE_CASE_ : int ) -> bool:
"""simple docstring"""
_UpperCAmelCase = str(SCREAMING_SNAKE_CASE_ )
return len(SCREAMING_SNAKE_CASE_ ) == 9 and set(SCREAMING_SNAKE_CASE_ ) == set('''12... | 32 | 0 |
'''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
lowerCAmelCase_ = logging.getLogger(... | 426 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_... | 426 | 1 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__magic_name__ = 10
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int... | 576 | from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
__magic_name__ = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
__magic_name__ = typing.Union[np.floataa, int, float] # noqa: UP007
def Upper... | 576 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
a = {"tokenization_byt5": ["ByT5Tokenizer"]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
a = _LazyModule(__name__, globals()[... | 703 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
__SCREAMING_SNAKE_CAS... | 13 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_param... | 176 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
A : List[Any] = argparse.ArgumentParser()
parser.add_argument('''--dump_path''', defau... | 176 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_i... | 721 |
'''simple docstring'''
import baseaa
def lowerCamelCase ( lowerCamelCase : str):
return baseaa.aaaencode(string.encode("""utf-8"""))
def lowerCamelCase ( lowerCamelCase : bytes):
return baseaa.aaadecode(lowerCamelCase).decode("""utf-8""")
if __name__ ==... | 27 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase : Optional[Any] = {
"""configuration_roberta""": ["""ROBERTA_PRETRAINED_CONFIG... | 302 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""shi-labs/dinat-mini-in1k-2... | 558 | 0 |
"""simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __snake_case ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = "x" , UpperCamelCase__ = 10**-10 , UpperCamelCase__ = 1 , ) -> int:
"""simple docstring""... | 702 |
"""simple docstring"""
def __snake_case ( ) -> int:
"""simple docstring"""
return 1
def __snake_case ( UpperCamelCase__ ) -> int:
"""simple docstring"""
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __snake_case ( Upp... | 91 | 0 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
fro... | 661 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int = 10 ) -> str:
if not isinstance(lowercase_ , lowercase_ ) or n < 0:
raise ValueError('''Invalid input''' )
_lowerCamelCase = 10**n
_lowerCamelCase = 2_84_33 * (pow(2 , 7_83_04_57 ,... | 661 | 1 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def lowerCamelCase__ ( UpperCamelCase__ : Tuple ) -> Optional[in... | 721 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class Upper... | 541 | 0 |
'''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
f... | 275 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoCon... | 275 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCAmelCase (__UpperCamelCase : str ):
"""simple docstring"""
__UpperCamelCase , __UpperCamelCase =analyze_text(__UpperCa... | 296 | """simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class _lowercase ( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( ... | 296 | 1 |
import collections
import os
import re
from pathlib import Path
lowercase : List[Any] = """src/transformers"""
# Matches is_xxx_available()
lowercase : List[str] = re.compile(r"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowercase : int = re.com... | 302 |
'''simple docstring'''
import cmath
import math
def __UpperCamelCase ( lowercase_ : float , lowercase_ : float , lowercase_ : float , lowercase_ : float ):
"""simple docstring"""
a_ = math.radians(lowercas... | 536 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE :Union[str, Any] = {'''configuration_mmbt''': ['''MMBTConfig''']}
try:
if not is_torch_available():
raise OptionalDepende... | 119 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def UpperCAmelCase_ ( _... | 119 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ )-> list:
"""simple docstring"""
snake_case_ : List[str] = [0] * len(__magic_name__ )
for i in range(1 ,len(__magic_name__ ) ):
# use last results for bette... | 653 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_sched... | 653 | 1 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
__UpperCamelCase : Any = {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DP... | 700 |
import warnings
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 __magic_name__ ( __lowerCAmelCase):
A:... | 106 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import Counter
from random import random
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self ) -> int:
__lowerCamelCase : List[str] = {}
... | 13 |
'''simple docstring'''
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
A__ : Any = re.compile(R"""^(?P<major>\d+)""" R"""\.(?P<minor>\d+)""" R"""\.(?P<patch>\d+)$""")
@total_ordering
@data... | 13 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 705 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase : Optional[Any] = {
"conf... | 625 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_u... | 96 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
_SCREAMING_SNAKE_CASE : List[Any] = logging.getLogger(__name... | 400 | 0 |
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
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case ... | 705 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case : Any = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConf... | 657 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
cente... | 458 |
def __magic_name__ ( lowercase = 100 ) -> int:
"""simple docstring"""
lowercase_ : Dict = (n * (n + 1) // 2) ** 2
lowercase_ : List[str] = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
... | 458 | 1 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def __A (_SCREAMING_SNAKE_CASE : int = 8 ) ->Union[str, Any]:
"""simple docstring"""
lowerCAmelCase__ :Union[str, Any] ... | 700 |
"""simple docstring"""
import tensorflow as tf
from ...tf_utils import shape_list
class _lowerCAmelCase ( tf.keras.layers.Layer ):
"""simple docstring"""
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCA... | 560 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ :List[Any] = logging.get_logger(__name__)
UpperCamelCase__ :Optional[Any] = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main... | 355 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def A_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ ) -> np.ndarray:
_UpperCamelCase :str = int(np.ceil((x_end - xa) / step_... | 355 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ : List[Any] = {
'''configuration_altclip''': [
'''ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 156 |
'''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/LICEN... | 156 | 1 |
from ....utils import logging
__SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
class __magic_name__ ( snake_case ):
def __init__( self : List[Any] , lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Optional[Any]=None , lowerCa... | 348 |
def UpperCAmelCase__ ( __magic_name__ : int ):
'''simple docstring'''
lowerCAmelCase : Optional[int] = [1]
lowerCAmelCase , lowerCAmelCase , lowerCAmelCase : Optional[Any] = 0, 0, 0
lowerCAmelCase : Union[str, Any] = ug... | 348 | 1 |
"""simple docstring"""
A = {
'''a''': '''AAAAA''',
'''b''': '''AAAAB''',
'''c''': '''AAABA''',
'''d''': '''AAABB''',
'''e''': '''AABAA''',
'''f''': '''AABAB''',
'''g''': '''AABBA''',
'''h''': '''AABBB''',
'''i''': '''ABAAA''',
'''j''': '''BB... | 101 |
"""simple docstring"""
def __A ( a_ :int , a_ :float , a_ :float) -> float:
return round(float(moles / volume) * nfactor)
def __A ( a_ :float , a_ :float , a_ :float) -> float:
return round(floa... | 101 | 1 |
'''simple docstring'''
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
lowerCAmelCase : int = 'scheduler_config.json... | 3 |
"""simple docstring"""
from __future__ import annotations
class __UpperCAmelCase:
"""simple docstring"""
def __init__( self , snake_case__ ):
'''simple docstring'''
lowercase__ : str= data
low... | 218 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'
... | 718 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case : Union[str, Any] = {
'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}
try:
if not is_t... | 687 | 0 |
"""simple docstring"""
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
_lowerCAmelCase = """facebook/wmt19-en-de"""
_lowerCAmelCase = FSMTTokenizer.from_pretrained(mname)
# get the correct vocab sizes, etc. from the master model
_lowerCAm... | 259 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class a__ ( a_ ):
__lowerCAmelCase = (DDPMScheduler,)
def __magic_name__ ( self , **_a ):
lowercase : ... | 361 | 0 |
"""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,
... | 713 |
"""simple docstring"""
class snake_case_ :
"""simple docstring"""
def __init__( self , __a , __a ):
"""simple docstring"""
A__ = name
A__ = val
def __str__( self ):
"""simpl... | 554 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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_backbo... | 293 |
import math
import os
import sys
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = ''
try:
with open(_UpperCAmelCase , 'rb') as binary_file:
SCREAMING_SNAKE_CASE = binary_file.read()
for dat in data:
SCREAMING_SNAKE_CASE ... | 73 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import ... | 192 | """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 Gene... | 192 | 1 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
SCREAMING_SNAKE_CASE : Union[str, Any] = {
"""facebook/maskformer-sw... | 197 | from typing import Any
def __A ( _A ):
"""simple docstring"""
if not input_list:
return []
__a = [input_list.count(_A ) for value in input_list]
__a = max(_A ) # Gets the maximum count in the input list.
# Gets values of modes
return sorted({input_li... | 197 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Optional[int] = logging.get_logger(__name__)
__lowerCamelCase : Dict = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Lla... | 418 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__lowerCamelCase : Optional[int] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
im... | 418 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.