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 |
|---|---|---|---|---|
def __snake_case ( lowerCAmelCase_ ) -> list[list[int]]:
SCREAMING_SNAKE_CASE__ = []
if len(lowerCAmelCase_ ) == 1:
return [nums.copy()]
for _ in range(len(lowerCAmelCase_ ) ):
SCREAMING_SNAKE_CASE__ = nums.pop(0 )
SCREAMING_SNAKE... | 100 |
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,
StableDiffusionPipeline,
U... | 587 | 0 |
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase... | 354 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _lowerCamelCase( _a ):
lowercase_ : List[Any] = ... | 354 | 1 |
from __future__ import annotations
class A :
def __init__( self: Dict , _lowerCAmelCase: int ) -> None:
'''simple docstring'''
UpperCAmelCase_ =order
# a_{0} ... a_{k}
UpperCAmelCase_ =[1.0] + [0... | 54 |
"""simple docstring"""
from math import pi, sqrt, tan
def _lowerCAmelCase(a : float ) -> float:
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''' )
return 6 * side_length**2
def _lowerCAmelCase(a : float , a... | 255 | 0 |
'''simple docstring'''
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class __A ( UpperCAmelCase__ , UpperCAmelCase__ ):
a__ : Tuple = 1
... | 714 | '''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
#
# ... | 415 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Optional[int] = logging.get_logger(__name__)
a__ : Union[str, Any] = {
'''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/... | 589 |
from manim import *
class A__ ( __snake_case ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : Union[str, Any] ):
"""simple docstring"""
UpperCamelCase = Rectangle(height=0.5 ... | 280 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool
if TYPE_CHECKING:
from PIL import Image
class UpperCamelCase ( lowercase_ ):
lowercase = 'Salesforce/bl... | 705 | """simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowercase__( ):
lowercase_ : List[Any] = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
lowercase_ : int = parser.add_su... | 477 | 0 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,... | 48 |
'''simple docstring'''
import operator
def snake_case ( snake_case : list , snake_case : bool = False , snake_case : list | None = None ) -> list:
"""simple docstring"""
lowerCAmelCase = operator.lt if reverse else operator.gt
lowerCAmelCase =... | 284 | 0 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCamelCase__ (_UpperCAmelCase):
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output , args.con... | 444 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
a_ : int = {
'configuration_speecht5': [
'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SPEECHT5_PRETRAINE... | 444 | 1 |
"""simple docstring"""
class _lowerCAmelCase : # Public class to implement a graph
"""simple docstring"""
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ):
'''simple docstring'''
lowerCAmelCase__ ... | 93 | import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
... | 486 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( __snake_case : int = 4_00_00_00 ):
'''simple docstring'''
lowercase = [0, 1]
lowercase = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
... | 134 |
"""simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def _SCREAMING_SNAKE_CASE ( __snake_case : int ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 o... | 134 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
_snake_case : Tuple = {
"configuration_speech_to_text": ["SPEECH_TO_TEXT_P... | 53 |
'''simple docstring'''
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class __UpperCAmelCase :
__lowercase = None
def lowerCamelCase ( self ):
"""simple docstring"""
_snake_ca... | 495 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowercase : str = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""PoolFormerC... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase : Tuple = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""Jukebox... | 66 | 1 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CAS... | 635 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __lowerCAmelCase ( lowerCAmelCase__ , unittest.TestCase ):
low... | 175 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __snake_case ( __snake_case ):
UpperCAmelCase__ : List[str] = ['''image_processor''', '''tokenizer''']
UpperCAmelCase__ : Optional[Any] = '... | 719 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def A (__A : int ) -> bool:
"""simple docstring"""
UpperCAmelCase_ = int(number**0.5 )
return number == sq * sq
def A (__A : ... | 169 | 0 |
'''simple docstring'''
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_sub... | 38 | '''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... | 78 | 0 |
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_m... | 708 |
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 import PatchingSpec
from ...token... | 472 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
"""Ju... | 477 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
a__ = logging.get_logger(__name__) # pylint: disable=invalid-name
def lowercase ( SCREA... | 477 | 1 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("""repo_id""" , ["""canonical_dataset_name""", """org-name/dataset-name"""] )
@pytest.mark.parametrize("""path""" , ["""filename.csv""", """filename with blanks... | 247 |
import os
import string
import sys
A : Dict = 1 << 8
A : Dict = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
... | 247 | 1 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __UpperCAmelCase ( __lowerCAmelCase ):
A__ : Optional[int] = '''Speech2TextFeatureExtractor'''
A__ : Tuple = '''Speech2TextTokenizer'''
... | 530 | """simple docstring"""
from __future__ import annotations
from typing import Any
class __UpperCAmelCase :
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase = 0 ):
lowerCamelCase__ , lowerCamelCase__ =row, column
lowerCamelCase__ ... | 530 | 1 |
'''simple docstring'''
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spect... | 0 |
'''simple docstring'''
import sys
UpperCamelCase__ : int = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"6... | 0 | 1 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def lowercase__ ( _UpperCamel... | 280 |
def lowercase__ ( _UpperCamelCase) -> list:
"""simple docstring"""
if bit_count < 0:
raise ValueError('The given input must be positive')
# get the generated string sequence
UpperCamelCase = gray_code_sequence_string(_UpperCamelCase)
... | 280 | 1 |
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCamelCase__ = 300 # TEMPERATURE (unit = K)
def _UpperCamelCase (a__ :float , a__ :float , a__ :float , ):
"""simple docstring"""
if donor_conc <= 0:
ra... | 710 |
import argparse
import datetime
def _UpperCamelCase (a__ :str ):
"""simple docstring"""
UpperCamelCase__ = {
"""0""": """Sunday""",
"""1""": """Monday""",
"""2""": """Tuesday""",
"""3""": """Wednesday""",
... | 548 | 0 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def _UpperCAmelCase ( __lowerCamelCase : Union[str, Any]="ro" , __lowerCamelCase : Optional[Any]="en" , __lowerCamelCase : Optional[int]="wmt16" , __lowerCamelCase : Tuple=None ) -> ... | 224 |
"""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_schedule_with_warmu... | 224 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
if not is_torch_available():
raise OptionalDep... | 700 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}
class SCRE... | 218 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class lowercase__ ( nn.Module ):
__UpperCAmelCase = 42
__UpperCA... | 88 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : str = logging.get_logger(__name__)
snake_case_ : Any = {
"""google/vivit-b-16x2-kinetics400""": (
"""https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve... | 595 | 0 |
import datasets
from .evaluate import evaluate
a= "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={arXiv preprint arXiv:2103.06268},\n year={2021}\n}\n"
... | 707 | '''simple docstring'''
def _UpperCamelCase ( _a : int ):
"""simple docstring"""
if bit_count < 0:
raise ValueError('The given input must be positive' )
# get the generated string sequence
__UpperCamelCase : Dict = gray_code_sequence_string(_a )
#
# convert them t... | 287 | 0 |
'''simple docstring'''
from itertools import product
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int ):
lowercase = sides_number
lowercase = max_face_number * dice_number
lowercase = [0] * (max_total + 1)
lowercase = 1
... | 588 |
'''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 VaeImagePro... | 588 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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... | 352 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"google/pegasus-large": "https://huggingface.co/google/pegasus-large/resolve/main/config.json",
# See all PEGASUS models at htt... | 352 | 1 |
"""simple docstring"""
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
__UpperCamelCase : Union[str, Any] = TypeVar('''T''')
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int ):
return (position - 1) // 2
def _SCREAMING_SNAKE_... | 4 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( a_ ):
SCREAMING_SNAKE_CASE : Dict = (DDPMScheduler,)
def _SCREAMING_SNAKE_CASE ( self , **_SCREAMING_SNAKE_CASE ):
... | 284 | 0 |
"""simple docstring"""
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 (
ConditionalDetrConfig,
ConditionalDetrForObjectDetect... | 713 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterator... | 659 | 0 |
'''simple docstring'''
import argparse
import struct
import unittest
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : Optional[int] , lowerCAmelCase__ : bytes ) -> None:
'''simple docstring'''
_UpperCamelC... | 98 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"""vocab_file""": """vocab.json""",
"""tokenizer_config_file... | 317 | 0 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
fr... | 290 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class _UpperCamelCase (enum.Enum ):
s... | 290 | 1 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
lowerCAmelCase_ : Tuple = 300 # TEMPERATURE (unit = K)
def _SCREAMING_SNAKE_CASE ( UpperCamelCase__ : float , UpperCamelCase__ : float , UpperCa... | 442 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : str = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/conf... | 442 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
... | 704 |
'''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
... | 61 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE (A ) -> int:
"""simple docstring"""
lowercase__ = [[0 for _ in range(A )] for _ in range(m + 1 )]
for i in range(m + 1 ):
lowercase__ = 1
for n in range(m + 1 ):
for... | 460 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Tuple = {
'configuration_distilbert': [
... | 460 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase ... | 569 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase )
class __UpperCAmelCase (_UpperCAmelCase ):
# `task` is not a ClassVar si... | 569 | 1 |
"""simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
... | 52 | """simple docstring"""
from __future__ import annotations
def lowercase ( UpperCamelCase : list[float] ):
"""simple docstring"""
if len(UpperCamelCase ) < 2:
raise ValueError("Monogons and Digons are not polygons in the Euclidean space" )
if any(i <= 0 for i i... | 656 | 0 |
'''simple docstring'''
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase=5 ) -> int:
'''simple docstring'''
assert masked_i... | 13 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class __a ( nn.Module ):
__UpperCamelCase : int
__UpperCamelCase : jnp.dtype = jnp.floataa
def UpperCAmelCase__ ( self : List[Any] ):
'''simple docstring'''
__SC... | 13 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
# See all PEGASUS models at https://hug... | 6 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : List[Any] ):
'''simple docstring'''
lowerCAmelCase = [
... | 532 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase ={
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BlipConfig",
"Bli... | 709 |
def snake_case__ ( lowerCAmelCase_ = 1000000 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE =limit + 1
SCREAMING_SNAKE_CASE =[0] * limit
for first_term in range(1, lowerCAmelCase_ ):
for n in range(lowerCAmelCase_, lowerCAmelCase_, lowe... | 252 | 0 |
"""simple docstring"""
from __future__ import annotations
def a_ ( lowercase__ :list[int] ):
if not nums:
return 0
__lowerCamelCase = nums[0]
__lowerCamelCase = 0
for num in nums[1:]:
__lowerCamelCase ,__lowerCamelCase ... | 281 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class __snake_case (lowerCamel... | 281 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
'SenseTime/deformable-detr': 'https://huggingface.co/sensetime/deformable-detr/resolve/main/conf... | 236 | import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __UpperCAmelCase( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase ( self ):
"""simple docs... | 236 | 1 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
snake_case_ : Any = 1
snake_case_ : Optional[int] ... | 58 | class _a :
'''simple docstring'''
def __init__( self , __UpperCAmelCase ):
__A : List[str] = val
__A : str = None
__A : List[Any] = None
def __UpperCAmelCase( self , __UpperCAmelCase ):
if self.val:
... | 520 | 0 |
'''simple docstring'''
import baseaa
def _UpperCamelCase ( lowerCAmelCase__: str ) -> bytes:
return baseaa.baaencode(string.encode('utf-8' ) )
def _UpperCamelCase ( lowerCAmelCase__: bytes ) -> str:
return bas... | 238 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuan... | 238 | 1 |
"""simple docstring"""
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,
EfficientFormer... | 96 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
_lowercase = parse(importlib.metadata.version('torch'))
def __UpperCamelCase ( a : ... | 342 | 0 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_co... | 712 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowerCamelCase : Any = None
try:
import msvcrt
except ImportError:
lowerCamelCase : str = None
try:
import fcntl
except ImportError:
lowerCamelCase : Optional[Any] = ... | 649 | 0 |
'''simple docstring'''
def _a( ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Union[str, Any] =[3_1, 2_8, 3_1, 3_0, 3_1, 3_0, 3_1, 3_1, 3_0, 3_1, 3_0, 3_1]
SCREAMING_SNAKE_CASE__ : List[Any] =6
SCREAMING_SNAKE_CASE__ : Dict... | 296 |
'''simple docstring'''
# Algorithm for the pigeonhole sorting
def _a( UpperCamelCase__ : Optional[int] ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : int =min(UpperCamelCase__ ) # min() finds the minimum value
SCREAMIN... | 296 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = {
'andre... | 395 |
"""simple docstring"""
def A_ ( __lowercase ):
if not isinstance(__lowercase , __lowercase ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(__lowercase ) == 0:
raise ValueError('Input list must be a non empty list' )
if len(__lowercase ) == 1:
return... | 395 | 1 |
"""simple docstring"""
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
... | 437 |
"""simple docstring"""
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
... | 437 | 1 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase_ : Optional[Any] = 5_00_00
lowerCamelCase_ : Optional[int] = 50_00
lowerCamelCase_ , lowerCamelCase_ : int ... | 302 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class _UpperCAmelCase :
'''simple docstring'''
lowercase_ : int
lowercase_ : int
class _Uppe... | 302 | 1 |
from __future__ import annotations
import math
def UpperCAmelCase_ ( _UpperCAmelCase :int ) -> Optional[Any]:
'''simple docstring'''
if num <= 0:
A_ = f'{num}: Invalid input, please enter a positive integer.'
raise ValueError(_UpperCAmelCase ... | 188 |
_a : str = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_a : int = [{"""type""":... | 145 | 0 |
'''simple docstring'''
import argparse
import collections
import os
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_table.py
__magic_name__ ... | 708 |
__magic_name__ = {
"joule": 1.0,
"kilojoule": 1_0_0_0,
"megajoule": 1_0_0_0_0_0_0,
"gigajoule": 1_0_0_0_0_0_0_0_0_0,
"wattsecond": 1.0,
"watthour": 3_6_0_0,
"kilowatthour": 3_6_0_0_0_0_0,
"newtonmeter": 1.0,
"calorie_nutr": 4_1_8_6.8,
"kilocalorie_nutr": ... | 73 | 0 |
from math import factorial
UpperCamelCase = {str(d): factorial(d) for d in range(10)}
def lowerCamelCase_ ( _lowercase ) -> int:
return sum(DIGIT_FACTORIAL[d] for d in str(_lowercase ) )
def lowerCamelCase_ ( ) -> int:
__A ... | 520 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : Optional[int] = logging.get_logger(__name__)
__lowercase : Optional[int] = {
'''studio-ousia/luke-base''': '''https://huggingface.co/studio-ousia/luke-base/resolve/... | 422 | 0 |
"""simple docstring"""
def snake_case ( lowerCAmelCase_ ) -> List[str]:
_snake_case = []
_snake_case = set({'''(''', '''[''', '''{'''} )
_snake_case = set({''')''', ''']''', '''}'''} )
_snake_case = {'''{''': '''}''', '''[''': ''']''', '''... | 404 |
"""simple docstring"""
import math
import sys
def snake_case ( lowerCAmelCase_ ) -> int:
if number != int(lowerCAmelCase_ ):
raise ValueError('''the value of input must be a natural number''' )
if number < 0:
raise ValueError('''the value of input must not be a... | 404 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
lowerCAmelCase_ : Union[str, Any] = 'docs/source/en/_toctree.yml'
def _lowerCamelCase ( lowercase : Optional[int] ) -> List[str]:
_a = defaultdict(lo... | 692 | import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
snake_case = logging.get_logger(__name__)
snake_case = {
"Intel/dpt-large": "https://huggingface.co/Intel/dpt-large/resolve/main/config.json",
# See all DPT models at http... | 424 | 0 |
"""simple docstring"""
from __future__ import annotations
class _SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self , lowerCamelCase__ ) -> None:
lowercase__ : Union[str, Any] = data
lowercase__ : Dict = None
lowercase__ : D... | 700 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _SCREAMING_SNAKE_CASE ( __UpperCAmelCase ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase__( lowerCamelCase__ ) -> Optional[Any]:
rai... | 128 | 0 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
if digit_amount > 0:
return round(number - int(UpperCamelCase__ ) , UpperCamelCase__ )
return number - int(UpperCamelCase__ )
if __name__ == "__main__":
print(d... | 407 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__A =get_t... | 407 | 1 |
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_table,
)
fr... | 526 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = (DDPMScheduler,)
def snake_case_ ( self , **a__):
A__ = {
'''num_train_timesteps''': 1... | 526 | 1 |
'''simple docstring'''
def UpperCAmelCase_ ( lowerCamelCase_ ):
"""simple docstring"""
if bit_count < 0:
raise ValueError("The given input must be positive" )
# get the generated string sequence
lowerCAmelCase__ : Dict = gray_code_sequence_string(a_ )
#
# convert them to in... | 378 |
"""simple docstring"""
def __lowerCamelCase ( a_ : int = 50 ) -> int:
__SCREAMING_SNAKE_CASE :List[str] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in ... | 498 | 0 |
# 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... | 414 |
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_token... | 414 | 1 |
"""simple docstring"""
import os
import sys
import unittest
__A : List[Any] = 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_dummies # noqa: E402
from check_dummie... | 231 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A__ )
class _lowercase ( A__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : str = field(default=''... | 696 | 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_ava... | 712 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase_ )
class lowerCAmelCase ( lowerCamelCase_ ):
... | 327 | 0 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__a :Dict = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_pytorch': 'https://huggingfa... | 86 |
import os
_lowercase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = 0
lowerCAmelCase_ : Any = 0
while index < len(snake_case__) - 1:
... | 659 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import TensorType,... | 683 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {'''vocab_file''': '''vocab.jso... | 683 | 1 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licen... | 90 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
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
lowercase_ ... | 562 | 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_backbone_common import Backb... | 719 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
class _UpperCAmelCase ( low... | 485 | 0 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
__lowerCamelCase = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL:... | 467 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case = logging.get_logger(__name__)
... | 451 | 0 |
'''simple docstring'''
import gc
import threading
import time
import psutil
import torch
class UpperCamelCase__ :
'''simple docstring'''
def __init__( self ) -> Optional[int]:
__lowerCAmelCase : List[Any] = psutil.Process()
__lowerCAmelCase ... | 123 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_toke... | 123 | 1 |
"""simple docstring"""
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,
)
_lowercase = {
'''configuration_albert'... | 91 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class A :
_SCREAMING_SNAKE_CASE = field(
default="""codeparrot/codeparrot""" ,metadata={"""help""": """Model name or path of model to be trained."""} )
_SCREAMING_SNAKE_CASE = ... | 326 | 0 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
... | 226 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {'''configuration_ibert''': ['''IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''IBertConfig''', '''IBertOnnxConfig''']}
try:
if not is_torch_available():
raise ... | 226 | 1 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def __UpperCamelCase ( a : int , a : int , a : float = 1 / sqrt(2 ) ) ->IIRFilter:
snake_case = tau * frequency / samplerate... | 342 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
... | 342 | 1 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageI... | 317 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : int ) -> bool:
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertic... | 317 | 1 |
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 17 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tens... | 637 | 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
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''facebook/d... | 96 |
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impo... | 96 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmentation,
... | 37 |
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
import... | 37 | 1 |
"""simple docstring"""
class _A :
"""simple docstring"""
def __init__( self : Optional[Any] , A_ : Tuple , A_ : List[Any] , A_ : List[Any] ) -> Optional[int]:
__snake_case = name
__snak... | 721 | """simple docstring"""
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def SCREAMING_SNAKE_CASE ( snake_case, snake_case = True, snake_case = math.inf, snake_case = -math.inf, snake_case = math.inf, snake_case = -math... | 93 | 0 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_con... | 100 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
_lowercase = logging.get_logger(__name__)
class __A :
UpperCamelCase :Union[str, Any] = None
@experimental
def _A (UpperCamelCase : Lis... | 157 | 0 |
"""simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def _lowerCAmelCase ( lowerCamelCase__ : List[Any], lowerCamelCase__ : Any ... | 295 |
"""simple docstring"""
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _lowerCAmelCase ( lowerCamelCase__ : Any, lowerCamelCase__ : Optional[Any], lowerCamelCase__ : List... | 295 | 1 |
'''simple docstring'''
from __future__ import annotations
_a : Dict = list[tuple[int, int]]
_a : str = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, 0,... | 56 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='session' )
def _a () -> Union[str... | 56 | 1 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase ( metaclass=UpperCAmelCase__ ):
'''simple docstring'''
lowerCAmelCase_ = ['''sentencepiece''']
def __init__( self : Tuple , *__lowercase : Opti... | 139 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase__ ( _A , _A , _A ):
'''simple docstring'''
snake_c... | 139 | 1 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""kakaobrain/align-base""": """https://huggingface.co/kakaobrain... | 74 | from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowerCAmelCase__ :
'''simple docstring'''
lowerCAmelCase_ = 42
lowerCAmelCase_ = 42
class ... | 544 | 0 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MAX_SHARD_SIZE
... | 712 | from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __lt__( self : Optional[Any] , ... | 234 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__UpperCamelCase : Tuple = {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNe... | 328 |
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,... | 328 | 1 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
a = logging.get_logger... | 347 |
'''simple docstring'''
import numpy as np
def a_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> Tuple:
"""simple docstring"""
snake_case: ... | 347 | 1 |
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available(... | 15 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common impo... | 276 | 0 |
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def lowerCamelCase__ ( UpperCamelCase__ : ... | 707 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class UpperCamelCase_ ( unittest.TestCase ):
def lowerCAmelCase ( self ) -> List[Any]:
debug_launcher(test_script.main )
def ... | 541 | 0 |
"""simple docstring"""
import os
import sys
import unittest
lowercase_ = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dum... | 470 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 0 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 712 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...t... | 235 | 0 |
"""simple docstring"""
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->int:
"""simple docstring"""
return number | (1 << position)
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->int:
"""simple docstring"""
return number & ~(1 << position)... | 93 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowerCamelCase__ = '''src/diffusers'''
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(r''... | 381 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ =... | 712 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
def __A(lowerCAmelCase , lowerCAmelCase ) -> List[str]:
"""simple docstring"""
_UpperCamelCase ... | 202 | 0 |
from __future__ import annotations
import os
from typing import Any
import requests
_lowerCamelCase : Any = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
_lowerCamelCase : str = BASE_URL + ... | 184 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
to_channel_dimensio... | 184 | 1 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def UpperCAmelCase ( _lowerCamelCase : List[str] , _lowerCamelCase : Optional[Any] , _lowerCamelCase : Dict , _lowerCamelCase : Any=1_024... | 26 |
from __future__ import annotations
from fractions import Fraction
def UpperCAmelCase ( _lowerCamelCase : int , _lowerCamelCase : int ):
'''simple docstring'''
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num ... | 26 | 1 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def snake_case_ ( lowerCAmelCase_ : Any , lowerCAmelCase_ : str ):
__lowercase : Union[str, Any] ... | 149 |
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_xlnet import ... | 149 | 1 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCAmelCase_ ( __a , __a , __a , __a , __a = None , __a = None , __a = None , ) -> Any... | 705 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_xformers_avai... | 437 | 0 |
'''simple docstring'''
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info... | 8 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase ( SCREAMING_SNAKE_CASE__: Optional[Any], ... | 448 | 0 |
import math
def _lowerCamelCase ( A_ : int ) -> bool:
'''simple docstring'''
assert isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
retu... | 702 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase__( snake_case__ ):
'''simple docstring'''
snake_case__ = ['''image_processor''', '''tokenizer''']
snake_case__ = ''... | 582 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
A_ : int =list[list[float | int]]
def SCREAMING_SNAKE_CASE_ ( snake_case : Tuple , snake_case : Tuple )-> Matrix:
_lowerCamelCase = len(_SCREAMING_SNAKE_CASE... | 650 |
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
... | 311 | 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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set... | 708 |
'''simple docstring'''
def __snake_case (__UpperCAmelCase = 3 , __UpperCAmelCase = 7 , __UpperCAmelCase = 1000000 ):
"""simple docstring"""
lowerCamelCase_ : Any = 0
lowerCamelCase_ : Tuple = 1
for current_denominator in range(1 , limit + ... | 418 | 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,
is_vision_available,
)
lowerCamelCase__ : Union[st... | 238 |
"""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... | 238 | 1 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowerc... | 700 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""Yitu... | 14 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.