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"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
__UpperCAmelCase =logging.get_logger(__name__) # pylint: disable=invalid-name
class lowerCAmelCase... | 337 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''M... | 118 | 0 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0**9 ):
__a : Any = 1
__a : List[Any] = 2
__a : List[str] = 0
__a : Optional[int] = 0
__a : Dict = 0
while perimeter <= max_perimeter... | 326 |
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 __UpperCamelCase ( lowerCAmelCase__ ... | 326 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def _snake_case ( snake_case__ : str , snake_case__ : Any , snake_case__ : Any )... | 91 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConf... | 416 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
_lowerCamelCase = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"""
""" Distilla... | 718 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = """https://o... | 447 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=a_ )
class lowerCAmelCase_ ( a_ ):
__UpperCAmelCase = field(default='language-modeling' , ... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : Optional[Any] = {
"""configuration_megatron_bert""": ["""MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegatronBertConfig"""],
}
tr... | 349 | 1 |
'''simple docstring'''
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
... | 716 |
'''simple docstring'''
import os
import numpy
import onnx
def __A ( _SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : List[Any] ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : int = a.nam... | 564 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a = False
class _A ( unittest.TestCase ):
pas... | 518 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
a = {
"configuration_speecht5": [
"SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SPEECHT5_PRETRAINE... | 518 | 1 |
def lowercase ( _a ) -> int:
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def lowercase ( _a ) -> bool:
UpperCAmelCase_: Any = 0
UpperCAmelCase_: List[str] = number
while duplicate > 0:
UpperCAmelCase_: List[Any] =... | 704 |
from __future__ import annotations
_lowerCAmelCase = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
_lowerCAmelCase = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def lowercase ( _a ) -> list[float]:
UpperCAmelCase_: Dict = []
U... | 306 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_mo... | 3 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _lowerCAmelCase ( lowercase_ ):
"""simple do... | 654 | 0 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
__lowerCamelCase : Any = abs(_lowerCamelCase )
__lowerCamelCase : List[str] = 0
while n > 0:
res += n % 10
n //= ... | 366 | """simple docstring"""
import gc
import threading
import time
import psutil
import torch
class _snake_case :
def __init__( self : str ):
__lowerCamelCase : Optional[Any] = psutil.Process()
__lowerCamelCase : List[Any] = False
... | 366 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import fl... | 209 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 153 | 0 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUID... | 716 | from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCAmelCase :
_SCREAMING_SNAKE_CASE : torch.Tensor # [batch_size x 3]
_SCREAMING_SNAKE_CASE : torch.Tensor # [batch_size x 3]
_SCREAMING_SNAKE_CAS... | 476 | 0 |
import gc
import threading
import time
import psutil
import torch
class A_ :
def __init__( self ):
'''simple docstring'''
UpperCAmelCase = psutil.Process()
UpperCAmelCase = False
def _lowercase ( self ):
'''simpl... | 130 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
... | 130 | 1 |
'''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,
... | 706 |
'''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/licenses/LICENSE-... | 695 | 0 |
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
from accelerat... | 257 |
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 | 1 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms... | 545 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCas... | 545 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A = {
'''configuration_layoutlmv2''': ['''LAYOUTLMV2_PRE... | 52 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase__ ... | 616 | 0 |
"""simple docstring"""
import math
import qiskit
def UpperCAmelCase ( snake_case : int = 1 , snake_case : int = 1 , snake_case : int = 1 ):
if (
isinstance(snake_case , snake_case )
or isinstance(snake_case , ... | 439 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils i... | 439 | 1 |
"""simple docstring"""
import argparse
import os
import re
__lowerCAmelCase : Any = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
__lowerCAmelCase : Any = re.compile(R'''^(\s*)\S''')
# Pattern that matches `"ke... | 58 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, PartialState
... | 587 | 0 |
'''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
def UpperCamelCase__ ( self : str ):
_a = Rectangle(height=0.5 , width=0.5 )
_a ... | 521 |
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def _lowerCamelCase ( lowercase : Union[str, Any] , ... | 521 | 1 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class __lowerCAmelCase ( logging.LoggerAdapter ):
"""simple docstring"""
@staticmethod
def snake_case__ ( lowerCAmelCase__ : Tuple ) -> List[Any]:
'''simp... | 98 |
def __SCREAMING_SNAKE_CASE ( lowerCAmelCase: int , lowerCAmelCase: int ) -> Dict:
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCAmelCase , int(b / 2 ) ) * actual_power(lowerCAmelCase , int(b / 2 ) )
else:
return a * actual_power(low... | 300 | 0 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowercase ( __a ):
"""simple docstring"""
lowercase__ = ['''image_processor''', '''tokenizer''']
lowercase__ ... | 700 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''YituTech/c... | 296 | 0 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCAmelCase ( A ):
UpperCAmelCase_ = {}
UpperCAmelCase_ = job["started_at"]
UpperCAmelCase_ = job["completed_at"]
UpperCAmelCase_ ... | 162 |
def __lowerCAmelCase ( A , A , A , A ):
# Return True if there is node that has not iterated.
UpperCAmelCase_ = [False] * len(A )
UpperCAmelCase_ = []
queue.append(A )
UpperCAmelCase_ = True
while queue:
UpperCAmelCase_ ... | 162 | 1 |
"""simple docstring"""
def __lowercase ( lowerCamelCase_ : int = 1000000 ):
SCREAMING_SNAKE_CASE__ = limit + 1
SCREAMING_SNAKE_CASE__ = [0] * limit
for first_term in range(1 , lowerCamelCase_ ):
for n in range(lowerCamelCase_ , ... | 112 |
"""simple docstring"""
from __future__ import annotations
def __lowercase ( lowerCamelCase_ : list , lowerCamelCase_ : int , lowerCamelCase_ : int , lowerCamelCase_ : int ):
SCREAMING_SNAKE_CASE__ = []
SCREAMING_SNAKE_CASE__ ... | 112 | 1 |
'''simple docstring'''
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_tr... | 526 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
i... | 526 | 1 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class _A ( _UpperCAmelCase ):
"""simple docstr... | 702 | """simple docstring"""
import re
def SCREAMING_SNAKE_CASE ( snake_case):
return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]''', str_)]
def SCREAMING_SNAKE_CASE ( snake_case):
__snake_case = split_input(str_)
return "".j... | 93 | 0 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
UpperCAmelCase = datasets.utils.logging.get_logger(__name__)
class snake_case__ ( folder_based_builder.FolderBasedBuilderConf... | 666 | from ...configuration_utils import PretrainedConfig
UpperCAmelCase = {
"google/tapas-base-finetuned-sqa": (
"https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"
),
"google/tapas-base-finetuned-wtq": (
"https://huggingface.co/google/tapas... | 666 | 1 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class lowerCamelCase ( unittest.TestCase ):
@require_torch
def snake... | 714 |
from manim import *
class lowerCamelCase ( SCREAMING_SNAKE_CASE ):
def snake_case_ ( self : int ) -> Tuple:
_a : Optional[int] = Rectangle(height=0.5 , width=0.5 )
_a : Dict = Rectangle(height=0.25 , width=0... | 249 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
... | 76 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : list[int] , _SCREAMING_SNAKE_CASE : list[int] ) -> tuple[float, float]:
"""simple docstring"""
if not len(_SCREAMING_SNAKE_CASE ) == len(_SCREAMING_SNAKE_CASE ) == 3:
raise ValueError("Please... | 71 | 0 |
'''simple docstring'''
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 __lowerCamelCase ( _... | 715 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowerCamelCase ( __snake_case : i... | 687 | 0 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __a ( SCREAMING_SNAKE_CASE ):
@require_torch
def UpperCamelCase ( self : List[str])-> Union[str, Any]... | 354 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
... | 354 | 1 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class __a ( _snake_case ):
... | 13 |
'''simple docstring'''
import os
import string
import sys
a = 1 << 8
a = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 27,
"up": 65 + ARROW_KEY_FLAG,
"down": 66 + ARROW_KEY_FLAG,
"right": 67 + ARROW_KEY_FLAG,
"left": 68 + ARROW_KEY_FLAG,
"mod_int": 91... | 13 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Union[str, Any] = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/... | 452 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Union[str, Any] = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/... | 452 | 1 |
'''simple docstring'''
def _a ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
"""simple docstring"""
return abs(__lowerCAmelCase ) if a == 0 else greatest_common_divisor(b % a , __lowerCAmelCase )
def _a ( __lowerCAmelCase : int , ... | 502 |
'''simple docstring'''
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fa... | 502 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline... | 250 |
"""simple docstring"""
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class _lowerCamelCase ( a_ ):
def __init__( self : Optio... | 299 | 0 |
'''simple docstring'''
import argparse
import os
import subprocess
from packaging.version import Version, parse
from accelerate.commands.config.config_args import default_config_file, load_config_from_file
__A : Dict = 'Run commands across TPU VMs for initial setup before running `accelerate ... | 703 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 126 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
... | 31 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
_A = logging.get_logger(__name__)
class _lowerCamelCase ( a_ ):
def __init__( self : str , *UpperCamelCase : int , **Upper... | 299 | 0 |
'''simple docstring'''
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : list ) -> None:
'''simple docstring'''
lowercase : Union[str, Any] =set_counts
lowercase : Any =max(Up... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase =logging.get_logger... | 617 | '''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__a: Optional[int] = logging.get_logger(__name__)
__a: Any = {
"""t5-small""": """https://huggingface.co/t5-small/re... | 152 | 0 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def UpperCAmelCase_ ( lowercase__ ):
'''simple docstring'''
if num <= 0:
raise ValueError("math domain error" )
return quad(lowerca... | 41 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase_ ( lowercase__ ):
'''simple docstring'''
a_ =str(lowercase__ )
return len(lowercase__ ) == 9 and set(lowercase__ ) == set("123456789" )... | 41 | 1 |
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokeni... | 17 |
"""simple docstring"""
from sklearn.metrics import matthews_corrcoef
import datasets
lowercase_ : Tuple = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classif... | 572 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 713 |
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
from unilm.w... | 458 | 0 |
"""simple docstring"""
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
lowerCAmelCase__ ="scheduler_config.json"
class A__( __magic_name__ ):
lowerCAmel... | 482 |
"""simple docstring"""
def _a ( UpperCAmelCase__ ) -> int:
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
__SCREAMING_SNAKE_CASE = 0
while number:
... | 482 | 1 |
'''simple docstring'''
class a :
def __init__( self , __magic_name__ , __magic_name__ , __magic_name__ ) -> Optional[Any]:
_a = None
_a = None
_a = graph
self._normalize_graph(__magic... | 532 |
'''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/... | 532 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
"""funnel-transformer/small""": """https://huggingface.co/funnel-transformer/small/resolve/main/config.json"""... | 99 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Optional[Any] = {
"""configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}
try:
if not ... | 328 | 0 |
lowercase_ = [
'''Audio''',
'''Array2D''',
'''Array3D''',
'''Array4D''',
'''Array5D''',
'''ClassLabel''',
'''Features''',
'''Sequence''',
'''Value''',
'''Image''',
'''Translation''',
'''TranslationVariableLanguages''',
]
from .audio import Au... | 336 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase = None, UpperCAmel... | 336 | 1 |
import random
from .binary_exp_mod import bin_exp_mod
def a__ ( lowercase__ , lowercase__=1_0_0_0 ):
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
UpperCAmelCase_ ... | 54 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : str = {'''configuration_vit_msn''': ['''VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMSNConfig''']}
try:
if not is_torch_... | 578 | 0 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipeline_test,
nest... | 193 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json',
# See all WavLM models at htt... | 193 | 1 |
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
snake_case__ : str = 'src/transformers'
snake_c... | 278 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class __A( a ):
def __lt__( self , _snake_case ) -> Dict:
'''simple docstring'''
return self[-1] < other[-1]... | 219 | 0 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def __A... | 156 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCAmelCase_ : List[Any] = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encode... | 156 | 1 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def _A ( _lowercase ) -> Tuple:
"""simple docstring"""
monkeypatch.setattr('datasets.utils.deprecation_utils._emitted_deprecation_warnings' , set() )
@pytest.... | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowerCAmelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 259 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( lowerCAmelCase_ : int ,lowerCAmelCase_ : list[int] ,lowerCAmelCase_ : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(lowerCAmelCase_ : int ) -> int... | 720 |
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def SCREAMING_SNAKE_CASE__ ( lowerCAmelCase_ : int ) -> str:
""... | 153 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : List[Any] = logging.get_logger(__name__)
UpperCAmelCase_ : Dict = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/co... | 44 |
'''simple docstring'''
class UpperCAmelCase__ :
def __init__( self : Any,__A : Any,__A : Any,__A : Any ):
_lowerCamelCase : List[Any] = name
_lowerCamelCase : Union[str, Any] = value
_lowerCamelCase : str ... | 44 | 1 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
_snake_case = '\\n@misc{chen2021evaluating,\... | 704 |
'''simple docstring'''
import math
import unittest
def snake_case_ (UpperCamelCase : int ):
'''simple docstring'''
assert isinstance(UpperCamelCase , UpperCamelCase ) and (
number >= 0
), "'number' must been an int and positive"
... | 377 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__UpperCamelCase : str = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowercase__ ( UpperCamelCase_):
... | 248 |
"""simple docstring"""
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 Model... | 506 | 0 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
return getitem, k
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docs... | 705 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if "img_encoder.pos_embed" in name:
snake_case__ : Dict = ... | 127 | 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_mas... | 355 | '''simple docstring'''
import requests
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : str ) -> None:
'''simple docstring'''
UpperCAmelCase_ = {"Content-Type": "application/json"}
UpperCAmelCase_ = requests.post(snake... | 78 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils ... | 718 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTe... | 145 | 0 |
'''simple docstring'''
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
... | 262 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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 Confi... | 68 | 0 |
"""simple docstring"""
import argparse
import struct
import unittest
class lowercase__ :
'''simple docstring'''
def __init__( self : Tuple , _UpperCAmelCase : bytes ) -> None:
'''simple docstring'''
... | 14 |
"""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,
... | 14 | 1 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
__lowerCAmelCase = input('Enter image url: ').strip()
print(F'''Downloading image from {url} ...''')
__lowerCAmelCase = BeautifulSoup(requests.get(url).content, 'html.... | 201 |
import os
def a ( a = "matrix.txt" ) ->int:
'''simple docstring'''
with open(os.path.join(os.path.dirname(a ) , a ) ) as in_file:
SCREAMING_SNAKE_CASE = in_file.read()
SCREAMING_SNAKE_CASE = [[int(a ) for cell in row.split(''',''' )] for row in data.strip()... | 201 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Any = {
'''configuration_autoformer''': [
'''AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''AutoformerC... | 77 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 1 |
'''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 SCREAMING_SNAKE_CASE ( lowerCAmelCase__ : List[Any] , lowerCAmelCase__ : int) -> ... | 125 |
'''simple docstring'''
import math
A = 10
A = 7
A = BALLS_PER_COLOUR * NUM_COLOURS
def SCREAMING_SNAKE_CASE ( lowerCAmelCase__ : int = 20) -> str:
'''simple docstring'''
_lowercase : Union[str, Any] = math.comb(lowerCAmel... | 125 | 1 |
"""simple docstring"""
def _snake_case ( snake_case__ : list[list[int]] , snake_case__ : int , snake_case__ : int , snake_case__ : set ):
A , A = len(snake_case__ ), len(grid[0] )
if (
min(snake_case__ , snake_case__ ) < 0
... | 721 |
"""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 = {
'''configuration_clip''': [... | 22 | 0 |
'''simple docstring'''
def lowerCamelCase ( __lowerCamelCase : str , __lowerCamelCase : str ) ->str:
if not (isinstance(__lowerCamelCase , __lowerCamelCase ) and isinstance(__lowerCamelCase , __lowerCamelCase )):
raise ValueError("""longest_common_... | 314 |
'''simple docstring'''
from __future__ import annotations
import os
from collections.abc import Mapping
lowercase_ = tuple[int, int]
class a_ :
'''simple docstring'''
def __init__( self , A , A ) -> None:
_SCREAMING_SNAKE_CASE = ... | 314 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
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_configu... | 35 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> tuple[float, list[float]]:
UpperCamelCase = list(range(len(__UpperCamelCase ) ) )
UpperCame... | 35 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( a : list , a : int , a : int = 0 , a : int = 0 ):
a__ = right or len(a ) - 1
if left > right:
return -1
elif list_data[left] == key:
return left
... | 394 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Any = logging.get_logger(__name__)
__A : Union[str, Any] = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/GPTSAN-2.... | 394 | 1 |
import re
from filelock import FileLock
try:
import nltk
__A = True
except (ImportError, ModuleNotFoundError):
__A = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
def _S... | 710 |
'''simple docstring'''
from functools import lru_cache
@lru_cache
def _SCREAMING_SNAKE_CASE ( A : int ) -> int:
"""simple docstring"""
if num < 0:
raise ValueError('Number should not be negative.' )
return 1 if num in (0, 1) ... | 61 | 0 |
import csv
import tweepy
# Twitter API credentials
SCREAMING_SNAKE_CASE__ = ''''''
SCREAMING_SNAKE_CASE__ = ''''''
SCREAMING_SNAKE_CASE__ = ''''''
SCREAMING_SNAKE_CASE__ = ''''''
def A ( __UpperCamelCase ) -> None:
# authorize twitter, initialize tweepy
A__ ... | 9 |
SCREAMING_SNAKE_CASE__ = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],
'''G''': ['''C'''],
}
def A ( __UpperCamelCase , ... | 9 | 1 |
def SCREAMING_SNAKE_CASE__ ( __A=28_123 ) -> Optional[Any]:
_snake_case = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1 ):
sum_divs[k * i] += k + i
_snake_case = set()
_snake_case... | 712 |
'''simple docstring'''
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def SCREAMING_SNAKE_CASE__ ( __A , __A , __A , __A=5 ) -> Dict:
# Adapted from https://github.com/pytorch/fairseq/blob/master/fairseq/models/roberta/hub_inte... | 542 | 0 |
lowerCamelCase ="\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
lowerCamelCase =[{"type": "code", "content": I... | 285 |
from typing import Any
def SCREAMING_SNAKE_CASE_ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
_validation(
UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , )
... | 285 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
UpperCamelCase__ : Union[str, Any] = {'''configuration_dpt''': ['''DPT_PRETRAINE... | 701 |
'''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _UpperCamelCase ( low... | 178 | 0 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCAmelCase_ (lowercase__ : s... | 668 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
_UpperCAmelCase : str = {
"vocab_file": "vocab.json"... | 668 | 1 |
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
@require_optimum
@s... | 698 |
__A : dict[str, float] = {
"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":... | 698 | 1 |
from sklearn.metrics import mean_squared_error
import datasets
lowerCamelCase_ = """\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. and Blondel, M... | 318 |
"""simple docstring"""
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
__magic_name__ = logging... | 155 | 0 |
import colorsys
from PIL import Image # type: ignore
def a__ ( lowercase__ , lowercase__ , lowercase__ ):
'''simple docstring'''
UpperCAmelCase_ : List[Any] =x
UpperCAmelCase_ : List[Any] =y
for step in ran... | 700 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
__lowercase : Optional[int] =TypeVar("""T""")
def a__ ( lowercase__ ):
'''simple docstring'''
return (position - 1) // 2
def a__ ... | 550 | 0 |
'''simple docstring'''
def a ( __a , __a ) -> str:
'''simple docstring'''
if not (isinstance(__a , __a ) and isinstance(__a , __a )):
raise ValueError('''longest_common_substring() takes two strings for inputs''' )
UpperCamelCase__ :str ... | 189 |
'''simple docstring'''
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, S... | 189 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils im... | 708 |
from itertools import count
def UpperCamelCase( lowercase_ = 50 ) -> int:
'''simple docstring'''
snake_case_ = [1] * min_block_length
for n in count(lowercase_ ):
fill_count_functions.append(1 )
for block_length in range(lowercase_ , n + 1 ... | 161 | 0 |
from __future__ import annotations
def __UpperCamelCase ( A ):
UpperCamelCase__ = 0.00
UpperCamelCase__ = 0
for resistor in resistors:
if resistor <= 0:
UpperCamelCase__ = f"Resistor at index {index} has a negative or... | 415 | import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 415 | 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,
get_resize_output_image_size,
normalize,
rescale,
... | 398 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : str = logging.get_logger(__name__)
__A : str = {
"huggingface/autoformer-tourism-monthly":... | 398 | 1 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import ... | 107 | '''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase_ (snake_case__ ):
'''simple docstring'''
__UpperCamelCase: Union[str, Any] = (DDPMScheduler,)
def _A ( self : ... | 244 | 0 |
import string
def UpperCamelCase ( _A : str )-> None:
"""simple docstring"""
for key in range(len(string.ascii_uppercase ) ):
A__ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 711 |
import importlib
import inspect
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_config_docstrings.py
UpperCAmelCase_ : Optional[Any] = "src/transformers"
# This is to make sure the transform... | 232 | 0 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...tes... | 485 |
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 = {
'junnyu/roformer_... | 485 | 1 |
'''simple docstring'''
def A_ ( _lowerCAmelCase : str , _lowerCAmelCase : int ):
"""simple docstring"""
_lowerCamelCase : list[list[str]] = [[] for _ in range(snake_case_ )]
_lowerCamelCase : Optional[int] = key - 1
if k... | 702 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import H... | 11 | 0 |
"""simple docstring"""
from collections.abc import Callable
def lowercase (_lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ):
__lowerCAmelCase = a
__lowerCAmelCase = b
if function(__lowerCAmelCase ) == 0: # one of the a or b is a root for the function
... | 465 |
def _lowerCAmelCase ( __lowerCAmelCase = 200 ) -> int:
"""simple docstring"""
snake_case__ : Optional[int] = [1, 2, 5, 10, 20, 50, 100, 200]
snake_case__ : List[Any] = [0] * (pence + 1)
snake_case__ : str = 1 # base case: 1 w... | 252 | 0 |
"""simple docstring"""
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("dataset_size" , [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize("input_in_memory_max_size" , ["default", 0, 1_00 * 2**20, 9_00 * 2*... | 292 |
"""simple docstring"""
snake_case_ : str = [
"""DownloadConfig""",
"""DownloadManager""",
"""DownloadMode""",
"""StreamingDownloadManager""",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manag... | 292 | 1 |
'''simple docstring'''
from __future__ import annotations
def _SCREAMING_SNAKE_CASE (A ) -> list[int]:
"""simple docstring"""
lowercase__ = 2
lowercase__ = []
while i * i <= n:
if n % i:
i += 1
else:
... | 460 |
'''simple docstring'''
from __future__ import annotations
lowerCamelCase : List[str] = []
def _SCREAMING_SNAKE_CASE (A , A , A ) -> bool:
"""simple docstring"""
for i in range(len(A ) ):
if board[row][i] == 1:
retu... | 460 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 714 |
from importlib import import_module
from .logging import get_logger
_SCREAMING_SNAKE_CASE : Optional[int] = get_logger(__name__)
class UpperCAmelCase__ :
"""simple docstring"""
def __init__( self : Optional[int] , __lowerCamelCase : Optional[Any] , __lowerCam... | 472 | 0 |
'''simple docstring'''
from collections.abc import Sequence
from queue import Queue
class a__ :
def __init__( self , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase=None , _UpperCamelCase=None ):
"""simple docstring"... | 245 |
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
def _A ( snake_case ) -> str:
_lowercase ... | 245 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"facebook/data2vec-vision-base-ft": (
... | 704 |
def _SCREAMING_SNAKE_CASE ( __lowercase : str = "The quick brown fox jumps over the lazy dog" , ) -> bool:
"""simple docstring"""
__A = set()
# Replace all the whitespace in our sentence
__A = input_str.replace(""" """ , """""" )
for a... | 199 | 0 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__a = logging.getLogger(__name__)
__a ... | 30 |
from functools import reduce
__a = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'66896648950445244523161731856... | 30 | 1 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowercase__ ( UpperCamelCase_):
@staticmethod
@abstractmethod
def __A ( UpperCamelCase__ : ArgumentParser ):
'''simple docstring'''
raise ... | 34 | import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET... | 34 | 1 |
"""simple docstring"""
from collections import defaultdict
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> bool:
'''simple docstring'''
_lowerCamelCase : str = first_str.lower().strip()
_lowerCamelCase : Any = second_str.low... | 46 | from graphs.minimum_spanning_tree_kruskal import kruskal
def lowerCamelCase_ ( ):
'''simple docstring'''
UpperCamelCase__ = 9
UpperCamelCase__ = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
... | 240 | 0 |
from __future__ import annotations
def a ( A__ : list[list[int]] ) -> int:
"""simple docstring"""
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in range(1 , l... | 380 |
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
DPR_CO... | 380 | 1 |
'''simple docstring'''
import numpy
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Any , a_ : numpy.ndarray , a_ : numpy.ndarray ):
"""simple docstring"""
__snake_case = input_array
# Random ... | 69 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 0 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOut... | 379 | import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
inf... | 379 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import choice
def __magic_name__ ( __UpperCAmelCase ) -> Union[str, Any]:
'''simple docstring'''
return choice(__UpperCAmelCase )
def __magic_name__ ( __UpperCAmelCase , __UpperCA... | 109 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __a ( _snak... | 109 | 1 |
'''simple docstring'''
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
... | 713 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_UpperCAmelCase : str = {
"""configuration_gpt_neox_japanese""": ["""GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MA... | 474 | 0 |
'''simple docstring'''
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
UpperCamelCase__: Dict = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machi... | 127 |
'''simple docstring'''
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
UpperCamelCase__: str = logging.get_lo... | 127 | 1 |
"""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 (
BnbQuantizati... | 712 |
"""simple docstring"""
def UpperCamelCase ( _A , _A ) -> str:
lowercase : list[list[str]] = [[] for _ in range(_A )]
lowercase : Any = key - 1
if key <= 0:
raise ValueError("""Height of grid can't be 0 or negative""" )
i... | 348 | 0 |
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