code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : int = logging.get_logger(__name__)
snake_case__ : Dict = {
'''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json''',
}
... | 60 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCAmelCase = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/deformable_detr/cuda/ms_deform_im2col_cuda.c... | 295 | 0 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
_SCREAMING_SNAKE_CASE ... | 3 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __lowerCamelCase ( __lowerCA... | 3 | 1 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.... | 12 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
a : Dict = (720, 1280) # Height, Width
a : Tuple = (0.4, 0.6) # if height or width lower than this scale, drop it.
a : Dict = ... | 56 | 0 |
from __future__ import annotations
from typing import Any
class __lowerCAmelCase :
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ = 0 ) -> None:
'''simple docstring'''
a__ ,... | 148 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
fr... | 148 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__snake_case : List[Any] = TypeVar('KT')
__snake_case : Optional[int] = TypeVar('VT')
class lowerCamelCase ( Generic[KT, VT] ):
'''simple docstring'''
... | 134 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __lowerCamelCase ( __snake_case : str = "." ) -> Iterator[str]:
"""simple docstring"""
for dir_path, dir_names, filenames in os.walk(__snake_case ):
A__ : Li... | 134 | 1 |
def __lowerCAmelCase ( a__ , a__ , a__ ) -> int:
def count_of_possible_combinations(a__ ) -> int:
if target < 0:
return 0
if target == 0:
return 1
return sum(count_of_possible_combinations(target - item ) for item in array )
retu... | 354 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : str = {
'configuration_time_series_transformer': [
'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TimeSeriesTransformerConfig',
],
}
try:
... | 33 | 0 |
def A_ ( _lowerCAmelCase ) -> int:
UpperCamelCase : Union[str, Any] = [[0 for _ in range(_snake_case )] for _ in range(m + 1 )]
for i in range(m + 1 ):
UpperCamelCase : Optional[Any] = 1
for n in range(m + 1 ):
for k in range(1 , _snake_c... | 52 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transfor... | 315 | 0 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determi... | 352 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __lowerCamelCase ( __lowerCAmelCase : str , __lowerCAmelCase : dict ) -> str:
snake_case = BeautifulSoup(requests.get(__lowerCAmelCase , params=__lowerCAmelCase... | 3 | 0 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _UpperCamelCase ( lowercase__ , lowercase__=False ):
__SCREAMING_SNAKE_CASE : Tuple = OmegaConf.load(lowercase__ )
if display:
... | 9 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelForQ... | 147 | 0 |
'''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,
)
if is_sentencepiece_available(... | 311 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table i... | 311 | 1 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( __SCREAMING_SNAKE_CASE : int | str ):
"""simple docstring"""
lowercase_ : Optional[int] = str(__SCREAMING_SNAKE_CASE )
return n == n[::-1]
de... | 93 |
'''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
fr... | 93 | 1 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase_ ( __lowerCamelCase : str ,__lowerCamelCase : list[str] | None = None ,__lowerCamelCase : dict[str, float] | None = None ,__lowerCamelCase : bool = False ,):
lowercase_ :List[Any] = ... | 361 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_ut... | 147 | 0 |
'''simple docstring'''
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMi... | 237 |
'''simple docstring'''
from __future__ import annotations
import time
import numpy as np
__lowerCAmelCase : Optional[Any] =[8, 5, 9, 7]
__lowerCAmelCase : Optional[int] =[
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
__lowerCAmelCase : List[... | 237 | 1 |
"""simple docstring"""
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 i... | 202 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
f... | 202 | 1 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def _UpperCamelCase ( lowercase__ ):
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output , args.c... | 9 |
'''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
... | 83 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
UpperCAmelCase__ =... | 354 |
"""simple docstring"""
from timeit import timeit
UpperCAmelCase__ = {
'MALAYALAM': True,
'String': False,
'rotor': True,
'level': True,
'A': True,
'BB': True,
'ABC': False,
'amanaplanacanalpanama': True, # "a man a plan a canal panama"
}
# Ensure our test d... | 40 | 0 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor... | 29 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}
try:
if not is_torch_available():
raise OptionalDepen... | 29 | 1 |
import unittest
import numpy as np
import requests
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():... | 369 |
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
if index == r:
for j in range(__lowerCamelCase ):
print(data[j] , ... | 134 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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_ten... | 346 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
UpperCAmelCase_ = '\\n\n'
UpperCAmelCase_ = '\nPerplexity (PPL) is one of the most common me... | 346 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
_A = logging.get_logger(__name__)
class _lowerCamelCase ( __snake_case ):
def __init__( self : Optional[Any] , *UpperCamelCase :... | 362 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowercase_ ( __UpperCAmelCase ) -> List[str]:
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class _lowerCamelCase ( ... | 212 | 0 |
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,
)
A_ :Any = {'''configuration_xglm'... | 71 |
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class snake_case__(_UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
@register_to_config
... | 130 | 0 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
... | 288 |
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_inpu... | 288 | 1 |
'''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... | 2 |
import os
from datetime import datetime as dt
from github import Github
_a = [
'''good first issue''',
'''feature request''',
'''wip''',
]
def _a ( ) -> List[Any]:
"""simple docstring"""
__lowerCAmelCase: Dict = Github(os.envi... | 322 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from... | 337 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __UpperCAmelCase ( unittest.TestCase ):
'''simple docstring'''
... | 337 | 1 |
'''simple docstring'''
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
SCREAMING_SNAKE_CASE__ ... | 321 |
'''simple docstring'''
from __future__ import annotations
import math
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE ) -> None:
"""simple docstring"""
UpperCamelCase = size
# approximate the ov... | 321 | 1 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_spa... | 350 |
"""simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
fro... | 233 | 0 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .... | 2 |
"""simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
SCREAMING_SNAKE_CASE_ : int = [
'Prosecutor: "No videos were used in the crash investigation" ... | 335 | 0 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
def __init__(self , *__a , **__a ) -> None:
... | 335 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch... | 335 | 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 UpperCamelCase( __UpperCamelCase : Dict ,__UpperCamelCase : Dict ):
lowerCAmelCase_ : Optional[Any] = k_size... | 103 | '''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a: List[str] = logging.get_logger(__name__)
class UpperCAmelCase ( a__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = "encoder-decoder"
... | 198 | 0 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
... | 308 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __magic_name__ ( pl.LightningModule ):
def __init__( self , __snake_case ) -> List[Any]:
... | 308 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : str = logging.get_logger(__name__)
UpperCAmelCase : str = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __lowerC... | 95 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase ( _A ):
lowerCAmelCase_ = 384
... | 278 | 0 |
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 tokenizers
__snake_... | 78 | import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {'''vocab_file''': '''vocab.json'''}
__snake_case = {
'''vocab_file''': {
... | 78 | 1 |
from collections import namedtuple
lowerCamelCase__ = namedtuple("""from_to""", """from_ to""")
lowerCamelCase__ = {
"""cubicmeter""": from_to(1, 1),
"""litre""": from_to(0.001, 1000),
"""kilolitre""": from_to(1, 1),
"""gallon""": from_to(0.0_0454, 264.172),
"""cubicyard""": from_t... | 302 |
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""... | 302 | 1 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_... | 252 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_di... | 252 | 1 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
lowercase_ ... | 303 |
import sys
from collections import defaultdict
class __UpperCamelCase :
"""simple docstring"""
def __init__( self : Union[str, Any] ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Optional[int] = []
def UpperCAmelCas... | 303 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int ) -> list[int]:
if length <= 0 or not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise ValueError("""Length must be a positive integer.""" )
return [n * (2 * n - 1) for n in range... | 350 | '''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase ( UpperCAmelCase__ : List[Any] , UpperCAmelCase__ : Op... | 21 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, Tens... | 145 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json''',
... | 5 | 0 |
"""simple docstring"""
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_configura... | 202 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_lowerCAmelCase : List[str] = {"vocab_file": "vocab.txt", "tokenizer... | 202 | 1 |
from __future__ import annotations
class a__ :
"""simple docstring"""
def __init__( self , lowercase ) -> None:
'''simple docstring'''
A__ = data
A__ = None
A__ = None
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: ... | 68 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def UpperCamelCase_( snake_case : Tuple ):
'''simple docstring'''
snake_case_ = FileLock(str(tmpdir / "foo.lock" ) )
snake_cas... | 85 | 0 |
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase=False ):
"""simple docstring"""
if isinstance(lowerCAmelCase , lowerCAmelCase ) and isinstance(lowerCAmelCase , lowerCAmelCase ):
_lowerCAmel... | 369 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
A__ : int ={'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
... | 220 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_a... | 240 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class snake_case_ (lowerCamelCase_ ):
@staticmethod
@abstractmethod
def lowerCamelCase__( __snake_case :ArgumentParser ) -> Dict:
raise NotImplementedError()
@abstractme... | 240 | 1 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ... | 364 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# ===== initialization =====
_SCREAMING_SNAKE_CASE : List[Any] = Mock(... | 325 | 0 |
"""simple docstring"""
class SCREAMING_SNAKE_CASE__ :
def __init__( self : int , lowerCAmelCase_ : Any):
"""simple docstring"""
lowercase_ = n
lowercase_ = [None] * self.n
lowercase_ = 0 # index ... | 136 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __A ( lowerCAmelCase ):
'''simple docstring'''
lowerCAmelCase_ = """Speech2TextFeatureExtractor"""
lowerCAmelCase_ = """Speech2TextTokenizer... | 209 | 0 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
UpperCamelCase : List[str] = logging.get_logger(__name__)
UpperCamelCase : Tuple = {
"""google... | 345 | '''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, ... | 345 | 1 |
'''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.... | 145 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at ht... | 145 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
i... | 351 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def UpperCAmelCase ( lowerCamelCase_ :Callable[[int | float], int | float] , lowerCamelCase_ :int | float , lowerCamelCase_ :int | float , lowerCamelCase_ :int = 1_00 , ):
... | 8 | 0 |
'''simple docstring'''
def UpperCamelCase ( _lowerCamelCase : str , _lowerCamelCase : int ):
A__ = word.split()
def justify(_lowerCamelCase : list , _lowerCamelCase : int , _lowerCamelCase : int ) ->... | 237 |
'''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 UpperCAmelCase ( Uppe... | 237 | 1 |
'''simple docstring'''
from __future__ import annotations
def _A ( A__ , A__ , A__ , ):
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 values''' )
elif electron_conc... | 363 |
'''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__ = {
'''configuration_whisper''': ['''WHISPER_PR... | 52 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...... | 60 |
"""simple docstring"""
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class snake_case_... | 60 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobe... | 371 |
"""simple docstring"""
from __future__ import annotations
import bisect
def lowercase__ ( snake_case_ :list[int] , snake_case_ :int , snake_case_ :int = 0 , snake_case_ :int = -1 ):
if hi < 0:
__UpperCAmelCase = len(snake_case_ )
while lo < hi:
... | 86 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ : List[Any] = {"configuration_reformer": ["REFORMER_PR... | 165 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A_ : List[str] = {"configuration_yolos": ["YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP", "YolosConfig", "YolosOnnxConfig"]}
t... | 165 | 1 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
__UpperCamelCase : ... | 51 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _inte... | 51 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> float:
return round(float(moles / volume ) * nfactor )
def lowerCamelCase ( UpperCAmelCase__ ... | 239 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class __magic_name__ :
def __init__( self : str , lowercase_ : Dict ):
if isinst... | 239 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaF... | 371 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( A__ : int | float | str , A__ : int | float | str ):
'''simple docstring'''
if nth_term == "":
return [""]
lowerCAmelCase_ : str = i... | 89 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
UpperCamelCase_ = TypeVar('''T''')
class _snake_case ( Generic[T] ):
'''simple docstring'''
def __init__( self: List[str] ,lowerCamelCase_: li... | 345 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Dict = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""Jukeb... | 307 | 0 |
def _lowerCAmelCase ( __lowerCAmelCase = 1000 ) -> int:
"""simple docstring"""
snake_case__ , snake_case__ : List[Any] = 1, 1
snake_case__ : Union[str, Any] = 2
while True:
snake_case__ : Optional[int] = 0
... | 44 |
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():
... | 44 | 1 |
'''simple docstring'''
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from acc... | 297 |
from __future__ import annotations
def __lowerCamelCase ( UpperCAmelCase_ : dict , UpperCAmelCase_ : str ):
"""simple docstring"""
a , a :Optional[Any] = set(UpperCAmelCase_ ), [start]
while stack:
a :Optional[int... | 94 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_comm... | 354 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __A ( A_ ):
'''simpl... | 302 | 0 |
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.iterators import ThreadedIterator
from tqdm ... | 233 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 233 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
_SCREAMING_SNAKE_CASE : List[str] = log... | 371 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor... | 213 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, t... | 297 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accel... | 297 | 1 |
"""simple docstring"""
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 lowerCAmelCase__ ( folder_based_builder.F... | 40 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowerCAmelCase__ :
__a = 42
__a = 42
class lowerCAmelCase__ :
... | 40 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__magic_name__: Tuple = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the refe... | 342 |
__magic_name__: str = [0, 2, 4, 6, 8]
__magic_name__: Optional[int] = [1, 3, 5, 7, 9]
def UpperCamelCase ( _A, _A, _A, _A ):
"""simple docstring"""
if remaining_length == 0:
if digits[0] == 0 or digits[-1] == 0:
r... | 342 | 1 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class _UpperCAmelCase :
'''simple docstring'''
def __init__(self , a_ ):
'''simple docstring'''
__snake_case : Optional[int] = list_of_points
# Degree de... | 357 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.u... | 24 | 0 |
'''simple docstring'''
def snake_case_ ( __SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
if not isinstance(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase_ : Optional[int] = F'''Input... | 93 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
... | 93 | 1 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAP... | 195 |
"""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,
)
if is_sentencepiece_available():
from ..ta... | 195 | 1 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase... | 86 |
"""simple docstring"""
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 (
... | 86 | 1 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state... | 356 |
"""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-2.0
#
... | 74 | 0 |
from __future__ import annotations
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase=None ) -> Dict:
"""simple docstring"""
lowerCAmelCase__ : List[str] = data
lowerCAmelCase__ : List[str] ... | 129 |
# Function to print upper half of diamond (pyramid)
def lowerCAmelCase__ ( lowerCamelCase_ : Optional[int]):
'''simple docstring'''
for i in range(0 ,lowerCamelCase_):
for _ in range(0 ,n - i - 1): # printing spaces
print(''' ''' ,end='''''')
... | 129 | 1 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: str ):
"""simple docstring"""
return "".join(chr(ord(__UpperCamelCase ) - 32 ) if 'a' <= char <= 'z' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
... | 246 |
'''simple docstring'''
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import j... | 246 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils import FeatureExtracti... | 49 |
'''simple docstring'''
import random
from .binary_exp_mod import bin_exp_mod
def snake_case_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[Any]=1000 ) -> int:
if n < 2:
return False
if n % 2 == 0:
r... | 23 | 0 |
def _lowercase ( _UpperCAmelCase ) -> int:
lowerCamelCase =[[0 for _ in range(_UpperCAmelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
lowerCamelCase =1
for n in range(m + 1 ):
for k in range(1 , _UpperCAmelCase ):
memo[n][k] +=... | 262 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowercase ( _UpperCAmelCase = "isbn/0140328726" ) -> dict:
lowerCamelCase =olid.strip().strip("""/""" ) # Remove leading/trailing whitespace & slashes
if new_olid.count("... | 262 | 1 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as ... | 30 |
"""simple docstring"""
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common imp... | 40 | 0 |
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import tensorflow as tf
from tokenizers import... | 370 |
from scipy.stats import spearmanr
import datasets
_snake_case : Optional[Any] = "\nThe Spearman rank-order correlation coefficient is a measure of the\nrelationship between two datasets. Like other correlation coefficients,\nthis one varies between -1 and +1 with 0 implying no correlation.\nPositive ... | 134 | 0 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTe... | 319 | 1 |
"""simple docstring"""
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
snake_case : List[Any] = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(... | 367 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : List[Any] = {
"junnyu/roformer_chin... | 41 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
snake_case : Optional[int] = {
'''configuration_trocr''': ['''TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 94 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class _lowerCAmelCase ( __a ):
_lowercase ='''megatron-bert'''
def _... | 231 | 0 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
T... | 354 |
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 = {
'''YituTech/conv-bert-base''': '''https://h... | 211 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : List[Any] = {"configuration_plbart": ... | 224 |
"""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, ImageInput, make_list_of_... | 238 | 0 |
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 ... | 369 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def SCREAMING_SNAKE_CASE__ ( __a , __a=None ):
snake_case_ : Optional[int] = None
if token is not None:
snake_c... | 88 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/co... | 61 |
'''simple docstring'''
from typing import List
import numpy as np
def _A ( _lowerCAmelCase ):
"""simple docstring"""
__lowercase ={key: len(_lowerCAmelCase ) for key, value in gen_kwargs.items() if isinstance(_lowerCAmelCase , _lowerCAmelCase )}
... | 166 | 0 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _UpperCAmelCase( lowerCamelCase , unittest.TestCase ):
... | 351 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/config.json""",
# See all BioGPT mo... | 100 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : List[Any] = {
"""configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TimesformerConfig"""],
}
try:
if not is_torch_availa... | 99 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=UpperCamelCase ):
'''simple docstring'''
__A : Any = ["flax"]
def __init__( self , *__A , **__A ):
"""simple docstring"""
... | 283 | 0 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ = 1_0_0_0 )-> int:
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 350 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, lo... | 60 | 0 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
lowercase__ = "\\n@inproceedings{snover-etal-2006-study,\n title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",\n author = \"Snover, Matthew and\... | 151 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepen... | 46 | 0 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
UpperCAmelCase__ = TypeVar("T")
UpperCAmelCase__ = Union[List[T], Tuple[T, ...]]
UpperCAmelCase__ = Union[T, List[T], Dict[str, T]]
UpperCAmelCase__ = Union[str, bytes, os.PathLike]
| 290 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
UpperCAmelCase__ = {
# 1536-bit
5: {
"prime": int(
"FFFFFFFFFFFF... | 290 | 1 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow ... | 203 |
"""simple docstring"""
def __lowerCAmelCase ( lowercase : int ) -> bool:
"""simple docstring"""
if p < 2:
raise ValueError("p should not be less than 2!" )
elif p == 2:
return True
snake_case : Dict = 4
snake_case : str ... | 203 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(_a ) ... | 370 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 72 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, BlipImageProcessor, Bli... | 20 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 ImageProcessingS... | 119 | 0 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
_snake_case : List[Any] = logging.get_logger(__name__)
_snake_case : Optional[int] = ... | 371 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Union[str, Any] = logging.get_logger(__name__)
_snake_case : List[str] = {
"facebook/encodec_24khz": "https://huggingface.co/fac... | 134 | 0 |
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from transformers impor... | 340 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
A = logging.get_logger(__name__)
def __A ( a_ :Tuple) -> Tu... | 160 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def UpperCamelCase ( a , a ) -> list:
'''simple docstring'''
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('''Matrices are not 2x2''' )
... | 98 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
def UpperCamelCase ( a , a ) -> bool:
'''simple docstring'''
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def Up... | 98 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
Au... | 66 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 66 | 1 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state imp... | 24 |
"""simple docstring"""
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impor... | 24 | 1 |
"""simple docstring"""
import warnings
from functools import wraps
from typing import Callable
def UpperCamelCase_ ( lowerCAmelCase__ : Callable ) -> Callable:
"""simple docstring"""
@wraps(lowerCAmelCase__ )
def _inner_fn(*lowerCAmelCase... | 224 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] ) -> Optional[int]:
"""simple docstring"""
lowerCAmelCase_ : Tuple = [0] * len(lowerCAmelCase__ )
lowerCAmelCase_ : List[str] = []
lowerCA... | 224 | 1 |
"""simple docstring"""
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
lowerCAmelCase_ = 'src/transformers'
# Th... | 302 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __lowerCamelCase ) -> str:
lowercase__ : Tuple = 0
lowercase__ : Tuple = 0
while num > 0:
lowercase__ : int = num % 8
lowercase__ : Tu... | 302 | 1 |
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
UpperCamelCase = False
class snake_case_ ( unittest.TestCa... | 87 | '''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def a ( self : int ) -> Optional[Any]:
return ... | 229 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( a_: Tuple ):
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
8: [5, 7],
},
... | 17 | '''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
... | 17 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
class _UpperCAmelCase ( __snake_case ):
'''simple docstring'''
def __init__(self , *a_ ... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase : Any = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git... | 167 | 0 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
D... | 350 |
'''simple docstring'''
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
... | 55 | 0 |
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