code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from ac... | 612 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def lowerCAmelCase ( UpperCamelCase_: Dict ) -> Any:
'''simple docstring'''
_a = os.path.jo... | 612 | 1 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase ( UpperCamelCase_: int = 100 ) -> int:
'''simple docstring'''
return sum(map(UpperCamelCase_ , str(factorial(UpperCamelCase_ ) ) ) )
if __name__ == "__main__":
... | 612 |
"""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_MA... | 612 | 1 |
"""simple docstring"""
import numpy
# List of input, output pairs
UpperCamelCase = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
UpperCamelCase = (((515, 22, 13), 555), ((61, 35, 49), 150))
UpperCamelCase ... | 612 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 612 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase_ (_UpperCAmelCase, unittest... | 612 |
"""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_t... | 612 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlow... | 612 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (_UpperCAmelCase ):
def __init__( self , *a_ , **a_ ) ->No... | 612 | 1 |
"""simple docstring"""
from PIL import Image
def lowerCAmelCase ( UpperCamelCase_: Image , UpperCamelCase_: int ) -> Image:
'''simple docstring'''
_a = (259 * (level + 255)) / (255 * (259 - level))
def contrast(UpperCamelCase_: ... | 612 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from t... | 612 | 1 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...tes... | 612 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_... | 612 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logg... | 612 | 1 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: int , UpperCamelCase_: int ) -> int:
'''simple docstring'''
return number | (1 << position)
def lowerCAmelCase ( UpperCamelCase_: int , UpperCamelCase_: ... | 612 |
"""simple docstring"""
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from p... | 612 | 1 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: int ) -> bool:
'''simple docstring'''
_a = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCAmelCase ( UpperCamelCase_: int = 5000 ) -> ... | 612 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: Optional[int] , UpperCamelCase_: str ) -> List[Any]:
'''simple docstring'''
_a = (boundary[1] - boundary[0]) / steps
_a = boundary[0]
_a = boundary[1]
_a = ... | 612 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""microsoft/git-base""": """https://huggingface.co/m... | 612 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_mo... | 612 | 1 |
"""simple docstring"""
import numpy as np
def lowerCAmelCase ( UpperCamelCase_: np.array ) -> np.array:
'''simple docstring'''
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 612 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Tuple = (KDPMaDiscreteScheduler,)
A__ : Tuple ... | 612 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
"""configuration_upernet""": ["""UperNetConfig"""],
}
try:
if not is_torch_available():
raise OptionalDependen... | 612 |
"""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.... | 612 | 1 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: list[int] ) -> list[int]:
'''simple docstring'''
_a = len(UpperCamelCase_ )
for i in range(UpperCamelCase_ ):
for j in range(i + 1 , UpperCamelCase_ ):
if numbers... | 612 |
"""simple docstring"""
import math
def lowerCAmelCase ( UpperCamelCase_: int ) -> list:
'''simple docstring'''
_a = [True] * n
_a = False
_a = False
_a = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
... | 612 | 1 |
"""simple docstring"""
UpperCamelCase = """Input must be a string of 8 numbers plus letter"""
UpperCamelCase = """TRWAGMYFPDXBNJZSQVHLCKE"""
def lowerCAmelCase ( UpperCamelCase_: str ) -> bool:
'''simple docstring'''
if... | 612 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sage... | 612 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (_UpperCAmelCase ):
def __init__( self , *a_ , **a_ ) ->No... | 612 |
"""simple docstring"""
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Union[str, Any] = (PNDMScheduler,)
A__ : Optional[int] = (('''num_inferenc... | 612 | 1 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfAr... | 612 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCamelCase = TypeVar("""T""")
UpperCamelCase = TypeVar("""U""")
class lowercase_ (Generic[T, U] ):
def __init__( ... | 612 | 1 |
"""simple docstring"""
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
UpperCamelCase = logging.ge... | 612 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSche... | 612 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowercase_ (unittest.TestCas... | 612 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_commo... | 612 | 1 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class lowercase_ (_UpperCAmelCase ):
def __init__( self , a_ , a_=None , a_=Tr... | 612 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase_ (metaclass=_UpperCAmelCase ):
A__ : Any = ['''torch''', '''torchsde''']
def __init__( self , *a_ , **a_ ) ->Optional[int]:
'''simple docstr... | 612 | 1 |
"""simple docstring"""
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCamelCase = """src/transformers... | 612 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase ( UpperCamelCase_: ndarray ) -> float:
'''simple docstring'''
return np.dot(UpperCamelCase_ , Uppe... | 612 | 1 |
"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
UpperCamelCase = get_logger(__name__)
class lowercase_ (enum.Enum ):
A__ : Optional[int] = '''all_check... | 612 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {"""configuration_fnet""": ["""FNET_PRETRAINED_CONFIG_... | 612 | 1 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaP... | 612 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def lowerCAmelCase ( UpperCamelCase_: Dict ) -> Any:
'''simple docstring'''
_a = os.path.jo... | 612 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@da... | 612 |
"""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_MA... | 612 | 1 |
"""simple docstring"""
import random
def lowerCAmelCase ( UpperCamelCase_: int ) -> bool:
'''simple docstring'''
_a = num - 1
_a = 0
while s % 2 == 0:
_a = s // 2
t += 1
for _ in range(5 ):
_a = random.r... | 612 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 612 | 1 |
"""simple docstring"""
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCamelCase = 4
UpperCamelCase = 3
class lowe... | 612 |
"""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_t... | 612 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
"""configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}
try:
if not is_torch_av... | 612 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (_UpperCAmelCase ):
def __init__( self , *a_ , **a_ ) ->No... | 612 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_rober... | 612 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from t... | 612 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCAmelCase ( UpperCamelCase_: Dict ) -> Any:
'''simple docstring'''
return DownloadCommand(args.model , args.cache_dir , args.force ... | 612 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
... | 612 | 1 |
"""simple docstring"""
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 transf... | 612 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logg... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase = {
"""susnato/ernie-m-base_pytorch""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json""",
"""susnato/... | 612 |
"""simple docstring"""
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from p... | 612 | 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/LICEN... | 612 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: Optional[int] , UpperCamelCase_: str ) -> List[Any]:
'''simple docstring'''
_a = (boundary[1] - boundary[0]) / steps
_a = boundary[0]
_a = boundary[1]
_a = ... | 612 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils impor... | 612 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_mo... | 612 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERende... | 612 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Tuple = (KDPMaDiscreteScheduler,)
A__ : Tuple ... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase_: list[int] ) -> int:
'''simple docstring'''
if not nums:
return 0
_a = nums[0]
_a = 0
for num in nums[1:]:
_a , _a = (
... | 612 |
"""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.... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase_: list[int] , UpperCamelCase_: int ) -> int:
'''simple docstring'''
if len(UpperCamelCase_ ) < k or k < 0:
raise ValueError("Invalid Input"... | 612 |
"""simple docstring"""
import math
def lowerCAmelCase ( UpperCamelCase_: int ) -> list:
'''simple docstring'''
_a = [True] * n
_a = False
_a = False
_a = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
... | 612 | 1 |
"""simple docstring"""
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Auto... | 612 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sage... | 612 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (_UpperCAmelCase ):
def __init__( self , *a_ , *... | 612 |
"""simple docstring"""
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Union[str, Any] = (PNDMScheduler,)
A__ : Optional[int] = (('''num_inferenc... | 612 | 1 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,... | 612 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCamelCase = TypeVar("""T""")
UpperCamelCase = TypeVar("""U""")
class lowercase_ (Generic[T, U] ):
def __init__( ... | 612 | 1 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_t... | 612 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSche... | 612 | 1 |
"""simple docstring"""
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_o... | 612 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_commo... | 612 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelF... | 612 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase_ (metaclass=_UpperCAmelCase ):
A__ : Any = ['''torch''', '''torchsde''']
def __init__( self , *a_ , **a_ ) ->Optional[int]:
'''simple docstr... | 612 | 1 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_a... | 612 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase ( UpperCamelCase_: ndarray ) -> float:
'''simple docstring'''
return np.dot(UpperCamelCase_ , Uppe... | 612 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
f... | 612 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {"""configuration_fnet""": ["""FNET_PRETRAINED_CONFIG_... | 612 | 1 |
"""simple docstring"""
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
im... | 612 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def lowerCAmelCase ( UpperCamelCase_: Dict ) -> Any:
'''simple docstring'''
_a = os.path.jo... | 612 | 1 |
"""simple docstring"""
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... | 612 |
"""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_MA... | 612 | 1 |
"""simple docstring"""
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils ... | 612 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 612 | 1 |
"""simple docstring"""
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, ... | 612 |
"""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_t... | 612 | 1 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import tr... | 612 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (_UpperCAmelCase ):
def __init__( self , *a_ , **a_ ) ->No... | 612 | 1 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 612 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from t... | 612 | 1 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sage... | 612 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
... | 612 | 1 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class lowercase_ :
def __init__( self ) ->List[Any]:
'''simple docstring'''
_a = {}
def lowerCamelCase__ ( s... | 612 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logg... | 612 | 1 |
"""simple docstring"""
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from tra... | 612 |
"""simple docstring"""
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from p... | 612 | 1 |
"""simple docstring"""
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configur... | 612 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: Optional[int] , UpperCamelCase_: str ) -> List[Any]:
'''simple docstring'''
_a = (boundary[1] - boundary[0]) / steps
_a = boundary[0]
_a = boundary[1]
_a = ... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
UpperCamelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def lowerCAmelCase ( UpperCamelCase_: str =... | 612 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_mo... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class lowercase_ :
def __init__( self , a_ ) ->Union[str, Any]:
'''simple docstring'''
_a = data
_a = None
... | 612 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Tuple = (KDPMaDiscreteScheduler,)
A__ : Tuple ... | 612 | 1 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_mo... | 612 |
"""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.... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCamelCase = TypeVar("""T""")
UpperCamelCase = TypeVar("""U""")
class lowercase_ (Generic[T, U] ):
def __init__( ... | 612 |
"""simple docstring"""
import math
def lowerCAmelCase ( UpperCamelCase_: int ) -> list:
'''simple docstring'''
_a = [True] * n
_a = False
_a = False
_a = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
... | 612 | 1 |
"""simple docstring"""
import warnings
from .generation import TFGenerationMixin
class lowercase_ (_UpperCAmelCase ):
# warning at import time
warnings.warn(
'''Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will '''
... | 612 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sage... | 612 | 1 |
"""simple docstring"""
from math import pow, sqrt
def lowerCAmelCase ( *UpperCamelCase_: float ) -> bool:
'''simple docstring'''
_a = len(UpperCamelCase_ ) > 0 and all(value > 0.0 for value in values )
return result
def lo... | 612 |
"""simple docstring"""
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Union[str, Any] = (PNDMScheduler,)
A__ : Optional[int] = (('''num_inferenc... | 612 | 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_t... | 612 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCamelCase = TypeVar("""T""")
UpperCamelCase = TypeVar("""U""")
class lowercase_ (Generic[T, U] ):
def __init__( ... | 612 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""huggingface/informer-tourism-monthly""": (
"""ht... | 612 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSche... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
UpperCamelCase = TypeVar("""KT""")
UpperCamelCase = TypeVar("""VT""")
class lowercase_ (Generic[KT, VT] ):
def __init__( self ... | 612 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_commo... | 612 | 1 |
"""simple docstring"""
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCamelCase = 300 # TEMPERATURE (unit = K)
def lowerCAmelCase ( UpperCamelCase_: float , UpperCamelCase_: float , UpperCamelCase_: float ... | 612 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase_ (metaclass=_UpperCAmelCase ):
A__ : Any = ['''torch''', '''torchsde''']
def __init__( self , *a_ , **a_ ) ->Optional[int]:
'''simple docstr... | 612 | 1 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSche... | 612 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase ( UpperCamelCase_: ndarray ) -> float:
'''simple docstring'''
return np.dot(UpperCamelCase_ , Uppe... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
import requests
UpperCamelCase = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked... | 612 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {"""configuration_fnet""": ["""FNET_PRETRAINED_CONFIG_... | 612 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_to... | 612 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def lowerCAmelCase ( UpperCamelCase_: Dict ) -> Any:
'''simple docstring'''
_a = os.path.jo... | 612 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
UpperCamelCase = logging.get_logger(__name__)
def lowerCAmelCase ( UpperCamelCase_: Union[tf.Tensor, np.ndarray] ) -> ... | 612 |
"""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_MA... | 612 | 1 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: str , UpperCamelCase_: str ) -> float:
'''simple docstring'''
def get_matched_characters(UpperCamelCase_: str , UpperCamelCase_: str ) -> str:
_a = []
_... | 612 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 612 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
... | 612 |
"""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_t... | 612 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""... | 612 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (_UpperCAmelCase ):
def __init__( self , *a_ , **a_ ) ->No... | 612 | 1 |
"""simple docstring"""
import os
def lowerCAmelCase ( UpperCamelCase_: Tuple ) -> Tuple:
'''simple docstring'''
_a = len(grid[0] )
_a = len(UpperCamelCase_ )
_a = 0
_a = 0
_a = 0
# Check vertically, ho... | 612 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from t... | 612 | 1 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase_ (_UpperCAmelCase, _UpperCAmelCase ):
@register_to_config
def __init__( self , *,
... | 612 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
... | 612 | 1 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: str , UpperCamelCase_: Optional[int] ) -> Optional[Any]:
'''simple docstring'''
_a = [0 for i in range(r + 1 )]
# nc0 = 1
_a = 1
for i in range(1 , n + 1 ):... | 612 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logg... | 612 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)... | 612 |
"""simple docstring"""
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from p... | 612 | 1 |
"""simple docstring"""
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Union[str, Any] = (PNDMScheduler,)
A__ : Optional[int] = (('''num_inferenc... | 612 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: Optional[int] , UpperCamelCase_: str ) -> List[Any]:
'''simple docstring'''
_a = (boundary[1] - boundary[0]) / steps
_a = boundary[0]
_a = boundary[1]
_a = ... | 612 | 1 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Tuple = (KDPMaDiscreteScheduler,)
A__ : Tuple ... | 612 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_mo... | 612 | 1 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: str ) -> str:
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 612 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Tuple = (KDPMaDiscreteScheduler,)
A__ : Tuple ... | 612 | 1 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDi... | 612 |
"""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.... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import 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, random_att... | 612 |
"""simple docstring"""
import math
def lowerCAmelCase ( UpperCamelCase_: int ) -> list:
'''simple docstring'''
_a = [True] * n
_a = False
_a = False
_a = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
... | 612 | 1 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowercase_ :
def __init__( self , a_ ) ->Dict:
'''simple docstring'''
_a = data
_a = None
_a = None
def lowerCAmelCase ( ... | 612 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sage... | 612 | 1 |
"""simple docstring"""
UpperCamelCase = 65_521
def lowerCAmelCase ( UpperCamelCase_: str ) -> int:
'''simple docstring'''
_a = 1
_a = 0
for plain_chr in plain_text:
_a = (a + ord(UpperCamelCase_ )) % MOD_A... | 612 |
"""simple docstring"""
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Union[str, Any] = (PNDMScheduler,)
A__ : Optional[int] = (('''num_inferenc... | 612 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {"""config... | 612 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCamelCase = TypeVar("""T""")
UpperCamelCase = TypeVar("""U""")
class lowercase_ (Generic[T, U] ):
def __init__( ... | 612 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available(... | 612 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSche... | 612 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
tr... | 612 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_commo... | 612 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/config.json""",
#... | 612 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase_ (metaclass=_UpperCAmelCase ):
A__ : Any = ['''torch''', '''torchsde''']
def __init__( self , *a_ , **a_ ) ->Optional[int]:
'''simple docstr... | 612 | 1 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
UpperCamelCase = """
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Sim... | 612 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase ( UpperCamelCase_: ndarray ) -> float:
'''simple docstring'''
return np.dot(UpperCamelCase_ , Uppe... | 612 | 1 |
"""simple docstring"""
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 Ac... | 612 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {"""configuration_fnet""": ["""FNET_PRETRAINED_CONFIG_... | 612 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
UpperCamelCase = """ht... | 612 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def lowerCAmelCase ( UpperCamelCase_: Dict ) -> Any:
'''simple docstring'''
_a = os.path.jo... | 612 | 1 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: Any ) -> bool:
'''simple docstring'''
_a = [int(SCREAMING_SNAKE_CASE_ ) for i in ip_va_address.split("." ) if i.isdigit()]
return len(SCREAMING_SNAKE_CASE_ ) == 4 and all(0 <= ... | 700 |
"""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_MA... | 612 | 0 |
from typing import Any
class lowercase_ :
def __init__( self , a_ ) ->Tuple:
'''simple docstring'''
_a = data
_a = None
class lowercase_ :
def __init__( self ) ->Tuple:
'''simple docstring'''
... | 701 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 612 | 0 |
"""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 impo... | 702 |
"""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_t... | 612 | 0 |
"""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,
)
from torch.uti... | 703 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (_UpperCAmelCase ):
def __init__( self , *a_ , **a_ ) ->No... | 612 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot import... | 704 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from t... | 612 | 0 |
"""simple docstring"""
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_a... | 705 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
... | 612 | 0 |
"""simple docstring"""
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.p... | 706 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logg... | 612 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
"configuration_speech_to_text": ["SPEECH_TO_TEXT_PRETRAINE... | 707 |
"""simple docstring"""
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from p... | 612 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 708 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: Optional[int] , UpperCamelCase_: str ) -> List[Any]:
'''simple docstring'''
_a = (boundary[1] - boundary[0]) / steps
_a = boundary[0]
_a = boundary[1]
_a = ... | 612 | 0 |
"""simple docstring"""
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
UpperCamelCase = logging.get_logger(__name__)
def lowerCAmelCase ( UpperCamelCase_: int ... | 709 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_mo... | 612 | 0 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCamelCase = "\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Method for... | 710 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ (_UpperCAmelCase ):
A__ : Tuple = (KDPMaDiscreteScheduler,)
A__ : Tuple ... | 612 | 0 |
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