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 |
|---|---|---|---|---|
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase_: list[int] , UpperCamelCase_: int ) -> Optional[int]:
'''simple docstring'''
if len(_lowerCAmelCase ) == 0:
return False
_a = len(_lowerCAmelCase ) // 2
... | 711 |
"""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 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase_ (UpperCamelCase_ ):
A__ : Union[str, Any] = ["""image_processor""", """tokenizer"""]
A__ : List[str] ... | 712 |
"""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 | 0 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowerCAm... | 713 |
"""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 | 0 |
"""simple docstring"""
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorSta... | 714 |
"""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 | 0 |
"""simple docstring"""
import math
from collections.abc import Callable
def lowerCAmelCase ( UpperCamelCase_: List[Any] , UpperCamelCase_: Dict , UpperCamelCase_: Tuple ) -> Union[str, Any]:
'''simple docstring'''
_a = xa
_... | 715 |
"""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 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import ca... | 716 |
"""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 | 0 |
def lowerCAmelCase ( UpperCamelCase_: Tuple , UpperCamelCase_: Optional[Any] ) -> str:
'''simple docstring'''
assert x is not None
assert y is not None
_a = len(_lowerCamelCase )
_a = len(_lowerCamelCase )
# declaring the... | 717 |
"""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 | 0 |
"""simple docstring"""
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: {
"... | 718 |
"""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 | 0 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
UpperCamelCase = WebClient(token=os.environ["""CI_SLACK_BOT_TOKEN"""])
def lowerC... | 719 |
"""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 | 0 |
"""simple docstring"""
from maths.prime_factors import prime_factors
def lowerCAmelCase ( UpperCamelCase_: int ) -> int:
'''simple docstring'''
if not isinstance(UpperCamelCase_ , UpperCamelCase_ ):
_a = f'''Input value of [number={n... | 720 |
"""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 | 0 |
"""simple docstring"""
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCAmelCase ( UpperCamelCase_: int , UpperCamelCase_: int , UpperCamelCase_: float = 1 / sqrt(2 ) ) -> List[str]:
'''simp... | 721 |
"""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 | 0 |
"""simple docstring"""
import requests
def lowerCAmelCase ( UpperCamelCase_: str , UpperCamelCase_: str ) -> Union[str, Any]:
'''simple docstring'''
_a = {"Content-Type": "application/json"}
_a = requests.post(snake_case__ ... | 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 TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
"""configuration_megatron_bert""": ["""MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegatronBertConfig"""],
}
try:
if not is_torch_available(... | 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"""
def lowerCAmelCase ( UpperCamelCase_: list[int] ) -> Optional[Any]:
'''simple docstring'''
_a = []
if len(UpperCamelCase_ ) == 1:
return [nums.copy()]
for _ in range(len(UpperCamelCase_ ) ):
_a = nu... | 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 inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floa... | 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 warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (lowercase__ ):
def __init__( self , *a_ , **a_ ) ->None:
''... | 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 argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logg... | 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 argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase ( UpperCamelCase_: Union[st... | 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_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {
"""configuration_funnel""": ["""FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FunnelConf... | 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 json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.dat... | 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 os
import time
import numpy as np
import onnxruntime as ort
UpperCamelCase = '''1'''
UpperCamelCase = '''0'''
UpperCamelCase = '''1'''
UpperCamelCase = ort.SessionOptions()
UpperCamelCase = ort.G... | 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 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def lowerCAmelCase ( UpperCamelCase_: List[Any] ) -> str:
'''simple docstring'''
if not is_accelerate_available():
... | 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 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase_ (__Uppe... | 711 |
"""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 | 0 |
"""simple docstring"""
def lowerCAmelCase ( ) -> Optional[Any]:
'''simple docstring'''
_a = 0
for i in range(1 , 1001 ):
total += i**i
return str(_lowercase )[-10:]
if __name__ == "__main__":
print(s... | 712 |
"""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 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common... | 713 |
"""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 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
fr... | 714 |
"""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 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffuser... | 715 |
"""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 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowercase_ :
A__ : Optional[str] = field(
default='''codeparrot/codeparrot''', metadata={'''help''': '''Model name or path of model to be trained.'''} )
... | 716 |
"""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 | 0 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCAmelCase ( UpperCamelCase_: int , UpperCamelCase_: int , UpperCamelCase_: float = 1 / sqrt(2 ) ) -> List[Any]:
'''simple docstring'''
_a... | 717 |
"""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 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def lowerCAmelCase ( ... | 718 |
"""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 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecode... | 719 |
"""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 | 0 |
"""simple docstring"""
UpperCamelCase = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-',... | 720 |
"""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 | 0 |
"""simple docstring"""
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
UpperCamelCase = logging.getLogger(__name__)
if is_to... | 721 |
"""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 | 0 |
"""simple docstring"""
import unittest
from transformers import XLMConfig, 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_commo... | 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 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from .... | 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"""
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase ( UpperCamelCase_: Optional[Any] , UpperCamelCase_:... | 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 unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVa... | 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 copy
import random
from transformers import CLIPTokenizer
class lowercase_ (_UpperCAmelCase ):
def __init__( self , *a_ , **a_ ) ->List[Any]:
'''simple docstring'''
super().__init__(*lowercase__ , **lowercase__ )
_a ... | 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"""
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... | 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"""
def lowerCAmelCase ( UpperCamelCase_: int ) -> Tuple:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
_a = 1
_a = 1
while repunit:
_a = (10 * repunit + 1) % divisor
repunit_... | 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 |
def lowerCAmelCase ( UpperCamelCase_: List[str] , UpperCamelCase_: List[str] ) -> List[str]:
'''simple docstring'''
_a = (boundary[1] - boundary[0]) / steps
_a = boundary[0]
_a = boundary[1]
_a = make_points(lowercase_ ... | 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"""
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase_: Tuple ) -> list[int]:
'''simple docstring'''
return [ord(__UpperCamelCase ) - 96 for elem in plain]
def lowerCAmelCase ( UpperCamelCa... | 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"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase = {
"""configuration_mega""": ["""MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegaConfig""", """MegaOnnxConfig"""],... | 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 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowercase_ (nn.Module ):
def __init__( self , a_ = 1_6 , a_ = 8_8 , a_ = None , a_ = 1 , a_ = 0.0 , a_ = 3... | 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 |
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
... | 711 |
"""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 | 0 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: str , UpperCamelCase_: bool = False ) -> str:
'''simple docstring'''
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
_a = f'''Expect... | 712 |
"""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 | 0 |
"""simple docstring"""
from statistics import mean
import numpy as np
def lowerCAmelCase ( UpperCamelCase_: list , UpperCamelCase_: list , UpperCamelCase_: list , UpperCamelCase_: int ) -> list:
'''simple docstring'''
_a... | 713 |
"""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 | 0 |
"""simple docstring"""
from random import shuffle
import tensorflow as tf
from numpy import array
def lowerCAmelCase ( UpperCamelCase_: int , UpperCamelCase_: Dict ) -> Dict:
'''simple docstring'''
_a = int(a__ )
assert noofclus... | 714 |
"""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 | 0 |
"""simple docstring"""
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLI... | 715 |
"""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 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase_: Optional[int] , UpperCamelCase_: int , UpperCamelCase_: List[str] , UpperCamelCase_: List[str] , UpperCamelCase_: Optional[int] , ) -> ... | 716 |
"""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 | 0 |
def lowerCAmelCase ( UpperCamelCase_: float , UpperCamelCase_: list[float] ) -> float:
'''simple docstring'''
if discount_rate < 0:
raise ValueError("Discount rate cannot be negative" )
if not cash_flows:
raise ValueError("Cash flows lis... | 717 |
"""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 | 0 |
"""simple docstring"""
import math
def lowerCAmelCase ( UpperCamelCase_: List[str] ) -> Tuple:
'''simple docstring'''
_a = []
_a = 2
_a = int(math.sqrt(_lowercase ) ) # Size of every segment
_a = [True] * (end + 1)
_a ... | 718 |
"""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 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 719 |
"""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 | 0 |
"""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 import tabl... | 720 |
"""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 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase_: float , UpperCamelCase_: float , UpperCamelCase_: float , ) -> tuple[str, float]:
'''simple docstring'''
if (stress, tangential_force, ... | 721 |
"""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 | 0 |
"""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 ac... | 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 dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowercase_ :
A__ : torch.Tensor # [batch_size x 3]
A__ : torch.Tensor # [batch_size x 3]
A__ : torch.Tensor # [batch_size x 3]
A__ : torch.Tensor # [batch_size x ... | 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"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class ... | 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 inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTes... | 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 argparse
import json
import subprocess
def lowerCAmelCase ( UpperCamelCase_: List[Any] , UpperCamelCase_: int ) -> Union[str, Any]:
'''simple docstring'''
_a = []
_a = (
f'''curl -H "Accept: application/vnd.github+jso... | 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"""
def lowerCAmelCase ( UpperCamelCase_: str , UpperCamelCase_: Dict , UpperCamelCase_: str ) -> Optional[int]:
'''simple docstring'''
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__sn... | 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"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
'''configuration_bigbird_pegasus''': [
'''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BigBirdPegasusC... | 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_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2C... | 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"""
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 lowercase_ (folder_based_builder.FolderBasedBu... | 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"""
UpperCamelCase = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
def lowerCAmelCase ( UpperCamelCase_: bytes ) -> bytes:
'''simple docstring'''
if not isinstance(_A , _A ):
_a ... | 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 |
def lowerCAmelCase ( ) -> List[Any]:
'''simple docstring'''
_a = []
_a = 1
while len(A_ ) < 1E6:
constant.append(str(A_ ) )
i += 1
_a = "".join(A_ )
return (
int(constant[0] )
* int(constant[9] )
... | 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 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase = logging.get_logger(__name__)
class lowercase_ (snake_case__, snake_case__ ):
... | 711 |
"""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 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class lowercase_ (_UpperCA... | 712 |
"""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 | 0 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
UpperCamelCase = logging.get_logger(__name__)
def lowerCAmelCase ( UpperCamelCase_: ... | 713 |
"""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 | 0 |
"""simple docstring"""
from collections.abc import Generator
from math import sin
def lowerCAmelCase ( UpperCamelCase_: bytes ) -> str:
'''simple docstring'''
if len(A__ ) != 32:
raise ValueError("Input must be of length 32" )
_a ... | 714 |
"""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 | 0 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from tran... | 715 |
"""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 | 0 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class lowercase_ (_Up... | 716 |
"""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 | 0 |
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase_: list , UpperCamelCase_: int , UpperCamelCase_: int , UpperCamelCase_: int ) -> list:
'''simple docstring'''
_a = []
_a , _a = input_list... | 717 |
"""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 | 0 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: Any ) -> Any:
'''simple docstring'''
_a = [0] * len(UpperCamelCase_ )
_a = []
_a = [1] * len(UpperCamelCase_ )
for values in graph.values():
for i in values:
indegre... | 718 |
"""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 | 0 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCamelCase = """"""
UpperCamelCase = """"""
UpperCamelCase = """"""
UpperCamelCase = 1 # (0 is vertical, 1 is horizontal)
def ... | 719 |
"""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 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase... | 720 |
"""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 | 0 |
"""simple docstring"""
import argparse
import os
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_task_guides.py
UpperCamelCase = """src/transformers"""
U... | 721 |
"""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 | 0 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase ... | 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 |
def lowerCAmelCase ( UpperCamelCase_: Tuple ) -> Optional[Any]:
'''simple docstring'''
assert column_title.isupper()
_a = 0
_a = len(_lowerCAmelCase ) - 1
_a = 0
while index >= 0:
_a = (ord(column_title[index] ) - 64... | 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"""
import unittest
from transformers import XLMConfig, 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_commo... | 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"""
from __future__ import annotations
import math
class lowercase_ :
def __init__( self , a_ ) ->List[Any]:
'''simple docstring'''
_a = size
# approximate the overall size of segment tree with given value
_a ... | 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 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""tokenization_biogpt""": [""... | 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 collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...t... | 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 logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCamelCase = logging.getLogger(__name__)
UpperCamelC... | 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 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_I... | 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 copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase = logging.get_l... | 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 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... | 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 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():
import... | 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 |
def lowerCAmelCase ( UpperCamelCase_: int = 1000 ) -> Optional[int]:
'''simple docstring'''
_a = 3
_a = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
return result
if __n... | 711 |
"""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 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase_ ... | 712 |
"""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 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_visio... | 713 |
"""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 | 0 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowercase_ :
pass
| 714 |
"""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 | 0 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_a... | 715 |
"""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 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCamelCase = {"""processing_wav2vec2_with_lm""": ["""Wav2Vec2ProcessorWithLM"""]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
... | 716 |
"""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 | 0 |
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase_: Union[str, Any] , UpperCamelCase_: List[str] ) -> List[Any]:
'''simple docstring'''
print(f'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(U... | 717 |
"""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 | 0 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowerCAmelCase ( UpperCamelCase_: Callable , UpperCamelCase_: float , UpperCamelCase_: float , UpperCamelCase_: float , UpperCamelCase_: float ) -> T... | 718 |
"""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 | 0 |
"""simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
UpperCamelCase = [
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight', 'time_em... | 719 |
"""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 | 0 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: Tuple ) -> str:
'''simple docstring'''
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise ValueEr... | 720 |
"""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 | 0 |
"""simple docstring"""
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase... | 721 |
"""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 | 0 |
"""simple docstring"""
from math import pi, sqrt, tan
def lowerCAmelCase ( UpperCamelCase_: float ) -> float:
'''simple docstring'''
if side_length < 0:
raise ValueError("surface_area_cube() only accepts non-negative values" )
return 6 * sid... | 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 |
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