code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase : Tuple = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDe... | 345 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : List[str] = {"""processing_layout... | 345 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase : List[Any] = logging.get_logger(__name__)
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( ... | 345 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Tuple = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:
if not... | 345 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : list , snake_case : list , snake_case : int ) -> list:
"""simple docstring"""
a : Optional[int] = len(snake_case )
a : str = [[0] * ... | 345 | '''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/da... | 345 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transf... | 345 | '''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
UpperCamelCase : Optional[Any] = logging.getLogger(__name__)
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Tuple = "masked_bert"
... | 345 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase ( a_ ):
... | 345 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Tuple = ["image_processor", "tokenizer"]
A : Any = "ViTIm... | 345 | '''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def SCREAMING_SNAKE_CASE__ ( snake_case : str... | 345 | 1 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from... | 345 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[str] , Uppe... | 345 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=a_ )
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : str ... | 345 | '''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
from ... | 345 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : Any = logging.get_logger(__name__)
UpperCamelCase : int = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/as... | 345 | '''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to... | 345 | 1 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def SCREAMING_SNAKE_CASE__ ( snake_case : int = 1_500_000 ) -> int:
"""simple docstring"""
a : defaultdict = defaultdict(snake_case )
a : Tuple = 2... | 345 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : int | float | str , snake_case : int | float | str ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
a : ... | 345 | 1 |
'''simple docstring'''
from collections.abc import Callable
def SCREAMING_SNAKE_CASE__ ( snake_case : Callable[[float], float] , snake_case : float , snake_case : float ) -> float:
"""simple docstring"""
a : float = ... | 345 | '''simple docstring'''
import torch
def SCREAMING_SNAKE_CASE__ ( ) -> str:
"""simple docstring"""
if torch.cuda.is_available():
a : int = torch.cuda.device_count()
else:
a : Any = 0
print(F"""Successfully ran on {num_gpus}... | 345 | 1 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableD... | 350 | '''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 345 | 0 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_... | 351 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : list[int | float] , snake_case : int , snake_case : int ) -> int | float:
"""simple docstring"""
if len(snake_case ) =... | 345 | 0 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
UpperCamelCase : str = argparse.ArgumentParser()
parser.add_argument(
"""--chec... | 352 | '''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 Accel... | 345 | 0 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
UpperCamelCase : Any = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""": """attention.self""",... | 353 | '''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils im... | 345 | 0 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tenso... | 354 | '''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, ... | 345 | 0 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
UpperCamelCase : Optional[int] = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def SCREAMING_SNAKE_CASE__ ( ) -> List[str]:
"""simple docstring"""
a : Tuple ... | 355 | '''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 345 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : bytes ) -> str:
"""simple docstring"""
return "".join([hex(__snake_case )[2:].zfill(2 ).upper() for byte in list(__snake_case )] )
def SCREAMING_SNAKE_CASE__ ( ... | 356 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( a_ , unittest.TestCase ):
"""simple docstring""... | 345 | 0 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
f... | 357 | '''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : int , snake_case : int ) -> bool:
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 345 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 358 | '''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 345 | 0 |
'''simple docstring'''
UpperCamelCase : List[Any] = """Input must be a string of 8 numbers plus letter"""
UpperCamelCase : Any = """TRWAGMYFPDXBNJZSQVHLCKE"""
def SCREAMING_SNAKE_CASE__ ( snake_case : str ) -> Tuple:
if not isinstance(... | 359 | '''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def SCREAMING_SNAKE_CASE__ ( snake_case : str , snake_case : float | Decimal , snake_case : float = 10**-10 ... | 345 | 0 |
'''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 : Union[str, Any] = ... | 360 | '''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_common impo... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase : int = """#"""
class UpperCamelCase :
"""simple docstring"""
def __init__( self : Optional[int]):
"""simple docstring"""
a : Dict = {}
... | 361 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : List[str] = {"""processing_layout... | 345 | 0 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax... | 362 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Tuple = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:
if not... | 345 | 0 |
'''simple docstring'''
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import... | 363 | '''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/da... | 345 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : Optional[int] ) -> Optional[int]:
"""simple docstring"""
a : Optional[int] = [0] * len(a_ )
a : Optional[int] = []
a : List[Any] = [1] * len(a_ )
... | 364 | '''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
UpperCamelCase : Optional[Any] = logging.getLogger(__name__)
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Tuple = "masked_bert"
... | 345 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 365 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 0 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common ... | 366 | '''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def SCREAMING_SNAKE_CASE__ ( snake_case : str... | 345 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_configuration_... | 367 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[str] , Uppe... | 345 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : Union[str, Any] = {'configuration_beit': ['BEIT_PRETRAINED_CONFIG_A... | 368 | '''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
from ... | 345 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : List[str] ) -> List[str]:
"""simple docstring"""
if not all(char in '01' for char in bin_string ):
raise ValueError('Non-binary value was passed to the function' )
if not ... | 369 | '''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to... | 345 | 0 |
'''simple docstring'''
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def ... | 370 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : int | float | str , snake_case : int | float | str ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
a : ... | 345 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelera... | 371 | '''simple docstring'''
import torch
def SCREAMING_SNAKE_CASE__ ( ) -> str:
"""simple docstring"""
if torch.cuda.is_available():
a : int = torch.cuda.device_count()
else:
a : Any = 0
print(F"""Successfully ran on {num_gpus}... | 345 | 0 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_... | 350 | '''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 345 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCamelCase ( u... | 351 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : list[int | float] , snake_case : int , snake_case : int ) -> int | float:
"""simple docstring"""
if len(snake_case ) =... | 345 | 0 |
'''simple docstring'''
import argparse
import os
import re
UpperCamelCase : Union[str, Any] = """src/transformers/models/auto"""
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCamelCase : List[Any]... | 352 | '''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 Accel... | 345 | 0 |
UpperCamelCase : int = frozenset(
[
"""prompt""",
"""height""",
"""width""",
"""guidance_scale""",
"""negative_prompt""",
"""prompt_embeds""",
"""negative_prompt_embeds""",
"""cross_attention_kwargs""",
]
)
UpperCamelCase : ... | 353 | '''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils im... | 345 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase : Dict = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenizat... | 354 | '''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, ... | 345 | 0 |
'''simple docstring'''
import os
import sys
import unittest
UpperCamelCase : str = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402... | 355 | '''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
UpperCamelCase : Optional[Any] = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/m... | 356 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( a_ , unittest.TestCase ):
"""simple docstring""... | 345 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Optional[Any] = {"""configuration_vit_msn""": ["""VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMSNConfig"""]}
try:
if not is_torch_available():
... | 357 | '''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : int , snake_case : int ) -> bool:
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 345 | 0 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def SCREAMING_SNAKE_CASE__ ( snake_case : Union[str, Any] ):
"""simple do... | 358 | '''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 345 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : str , snake_case : str ) -> float:
def get_matched_characters(snake_case : str , snake_case : str ) -> str:
a : Optional[int] = []
... | 359 | '''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def SCREAMING_SNAKE_CASE__ ( snake_case : str , snake_case : float | Decimal , snake_case : float = 10**-10 ... | 345 | 0 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Optional[int] = ['image_processor', 'tokenizer']
A : Opt... | 360 | '''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_common impo... | 345 | 0 |
'''simple docstring'''
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configu... | 361 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : List[str] = {"""processing_layout... | 345 | 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 SCREAMING_SNAKE_CASE__ ( snake_case : List[str] , snake_case :... | 362 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Tuple = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:
if not... | 345 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTester... | 363 | '''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/da... | 345 | 0 |
'''simple docstring'''
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch... | 364 | '''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
UpperCamelCase : Optional[Any] = logging.getLogger(__name__)
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Tuple = "masked_bert"
... | 345 | 0 |
'''simple docstring'''
import math
class UpperCamelCase :
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( self : Optional[int] , UpperCAmelCase_ : list[list[float]] , UpperCAmelCase_ : list[int]):
"""simple docstring"""
... | 365 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 0 |
'''simple docstring'''
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def SCREAMING_SNAKE_CASE__ ( snake_case : int ) -> List[str]:
"""simple docstring"""
# A local function to see if a do... | 366 | '''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def SCREAMING_SNAKE_CASE__ ( snake_case : str... | 345 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase : int = logging.get_logger... | 367 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[str] , Uppe... | 345 | 0 |
'''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_roberta... | 368 | '''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
from ... | 345 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : int ) -> int:
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ):
a : List[str] = F"""Input value of [number={number}] must be an integer"""
... | 369 | '''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to... | 345 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : Optional[int] = {
"""configuration_layoutlmv2""": ["""L... | 370 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : int | float | str , snake_case : int | float | str ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
a : ... | 345 | 0 |
'''simple docstring'''
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
UpperCamelCase : Tuple = ... | 371 | '''simple docstring'''
import torch
def SCREAMING_SNAKE_CASE__ ( ) -> str:
"""simple docstring"""
if torch.cuda.is_available():
a : int = torch.cuda.device_count()
else:
a : Any = 0
print(F"""Successfully ran on {num_gpus}... | 345 | 0 |
'''simple docstring'''
import math
def SCREAMING_SNAKE_CASE__ ( snake_case : Any , snake_case : Any ) -> int:
"""simple docstring"""
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y ... | 350 | '''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 345 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common... | 351 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : list[int | float] , snake_case : int , snake_case : int ) -> int | float:
"""simple docstring"""
if len(snake_case ) =... | 345 | 0 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class UpperCamelCase ( unittest.TestCase ):
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( self : Tup... | 352 | '''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 Accel... | 345 | 0 |
from __future__ import annotations
import math
import random
from typing import Any
class UpperCamelCase :
"""simple docstring"""
def __init__( self : str):
"""simple docstring"""
a : Optional[int] = []
a : str = 0
... | 353 | '''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils im... | 345 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase ( metaclass=a_ ):
"""simple docstring"""
A : Dict = ["onnx"]
def __init__( self : List[str] , *UpperCAmelCase_ : Tuple , **UpperCAmelCase_... | 354 | '''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, ... | 345 | 0 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 355 | '''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 345 | 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
from ... | 356 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( a_ , unittest.TestCase ):
"""simple docstring""... | 345 | 0 |
from math import ceil, sqrt
def SCREAMING_SNAKE_CASE__ ( snake_case : int = 1_000_000 ) -> Union[str, Any]:
"""simple docstring"""
a : List[str] = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limi... | 357 | '''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : int , snake_case : int ) -> bool:
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 345 | 0 |
'''simple docstring'''
import numpy as np
def SCREAMING_SNAKE_CASE__ ( snake_case : List[str] , snake_case : List[Any] , snake_case : Any = 1E-1_2 , snake_case : int = 100 , ):
"""simple docstring"""
assert n... | 358 | '''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 345 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : str ) -> Dict: # noqa: E741
a : Dict = len(_UpperCAmelCase )
a : Optional[int] = 0
a : Tuple = [0] * n
a : Dict = [False] * n
a : List[st... | 359 | '''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def SCREAMING_SNAKE_CASE__ ( snake_case : str , snake_case : float | Decimal , snake_case : float = 10**-10 ... | 345 | 0 |
'''simple docstring'''
import torch
def SCREAMING_SNAKE_CASE__ ( ) -> List[Any]:
"""simple docstring"""
if torch.cuda.is_available():
a : Union[str, Any] = torch.cuda.device_count()
else:
a : Dict = 0
print(F"""Succe... | 360 | '''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_common impo... | 345 | 0 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import req... | 361 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : List[str] = {"""processing_layout... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor,... | 362 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Tuple = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:
if not... | 345 | 0 |
'''simple docstring'''
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
UpperCamelCase : int = {
'sample_size': 32,
'in_channels': 3,
'out_channels': 3,
'layers_per_block': 2,
... | 363 | '''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/da... | 345 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class UpperCamelCase ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( self : Union[str, Any]):
... | 364 | '''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
UpperCamelCase : Optional[Any] = logging.getLogger(__name__)
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Tuple = "masked_bert"
... | 345 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : List[Any] = {
"""configuration_instructblip""": [
"""INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""InstructBlipC... | 365 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : Union[str, Any] , snake_case : Dict ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def SCREAMING_SNAKE_CASE__ ( ) -> ... | 366 | '''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def SCREAMING_SNAKE_CASE__ ( snake_case : str... | 345 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class UpperCamelCase ( lowerCamelCase_ ):
"""simple docstring"""
def __init__( self : Tuple , UpperCAmelCase_ : U... | 367 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[str] , Uppe... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCamelCase : Optional[Any] = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
... | 368 | '''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
from ... | 345 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from... | 369 | '''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to... | 345 | 0 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTra... | 370 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : int | float | str , snake_case : int | float | str ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
a : ... | 345 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Dict = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
... | 371 | '''simple docstring'''
import torch
def SCREAMING_SNAKE_CASE__ ( ) -> str:
"""simple docstring"""
if torch.cuda.is_available():
a : int = torch.cuda.device_count()
else:
a : Any = 0
print(F"""Successfully ran on {num_gpus}... | 345 | 0 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
UpperCamelCase : Tuple = True
except (ImportError, ModuleNotFoundError):
UpperCamelCase : int = False
if NLTK_AVAILABLE:
with FileLock(""".lock""") as lock:
n... | 350 | '''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 345 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_... | 351 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : list[int | float] , snake_case : int , snake_case : int ) -> int | float:
"""simple docstring"""
if len(snake_case ) =... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase : Any = {
'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-z... | 352 | '''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 Accel... | 345 | 0 |
from __future__ import annotations
import time
import numpy as np
UpperCamelCase : Union[str, Any] = [8, 5, 9, 7]
UpperCamelCase : int = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
UpperCamelCase : List[Any] = [
... | 353 | '''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils im... | 345 | 0 |
'''simple docstring'''
UpperCamelCase : Union[str, Any] = '''
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
UpperCamelCase : Union[str, Any] ... | 354 | '''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, ... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase : Tu... | 355 | '''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 345 | 0 |
'''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 : Any = logging.... | 356 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( a_ , unittest.TestCase ):
"""simple docstring""... | 345 | 0 |
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def SCREAMING_SNAKE_CASE__ ( snake_case : Any ) -> ... | 357 | '''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : int , snake_case : int ) -> bool:
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 345 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_... | 358 | '''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase : Union[str, Any] = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweis... | 359 | '''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def SCREAMING_SNAKE_CASE__ ( snake_case : str , snake_case : float | Decimal , snake_case : float = 10**-10 ... | 345 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_s... | 360 | '''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_common impo... | 345 | 0 |
'''simple docstring'''
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[Any]):
"""simple docstring"""
a : Optional[int] = 0
a : str = 0
a : Optional[int] = {}
def SCRE... | 361 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : List[str] = {"""processing_layout... | 345 | 0 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
UpperCamelCase : Dict = parse(importlib.metadata.version("""torch"""))
def SCREAMING_SNAKE_CASE__ ( snake_case ... | 362 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Tuple = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:
if not... | 345 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase ( metaclass=a__ ):
"""simple docstring"""
A : Dict = ["""flax"""]
def __init__( self : Tuple , *UpperCAmelCase_ : int , **UpperCAmelCase_ ... | 363 | '''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/da... | 345 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : list ) -> list:
"""simple docstring"""
def merge(snake_case : list , snake_case : list ) -> list:
def _merge():
while left and right:
... | 364 | '''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
UpperCamelCase : Optional[Any] = logging.getLogger(__name__)
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Tuple = "masked_bert"
... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : int = logging.get_logger(__name__)
UpperCamelCase : int = {
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config... | 365 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 0 |
'''simple docstring'''
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floa... | 366 | '''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def SCREAMING_SNAKE_CASE__ ( snake_case : str... | 345 | 0 |
'''simple docstring'''
import math
import sys
def SCREAMING_SNAKE_CASE__ ( snake_case : int ) -> str:
"""simple docstring"""
a : List[str] = ''''''
try:
with open(SCREAMING_SNAKE_CASE__ , 'rb' ... | 367 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[str] , Uppe... | 345 | 0 |
'''simple docstring'''
from statistics import mean
import numpy as np
def SCREAMING_SNAKE_CASE__ ( snake_case : int , snake_case : List[str] , snake_case : Optional[Any] , snake_case : Tuple ) -> list:
"""s... | 368 | '''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
from ... | 345 | 0 |
'''simple docstring'''
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE__ ( snake_case : str , snake_case : str ) -> Un... | 369 | '''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
UpperCamelCase : Dict = 'https://api.github.com'
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
UpperCamelCase : Optional[... | 370 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : int | float | str , snake_case : int | float | str ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
a : ... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
import requests
UpperCamelCase : str = set(
"""approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category ... | 371 | '''simple docstring'''
import torch
def SCREAMING_SNAKE_CASE__ ( ) -> str:
"""simple docstring"""
if torch.cuda.is_available():
a : int = torch.cuda.device_count()
else:
a : Any = 0
print(F"""Successfully ran on {num_gpus}... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE__ ( snake_case : Optional[Any] , snake_case : List[str] ) -> List[Any]:
"""simple docstring"""
a : Optional[int] = u
for i in range(1... | 350 | '''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 345 | 0 |
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