code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : list , _lowercase : list ) ->float:
'''simple docstring'''
_validate_point(_lowercase )
_validate_point(_lowercase )
if len(_lowercase ) != len(_lowercase ):
... | 709 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class __UpperCamelCase ( nn.Module ):
lowerCamelCase : int
lowerCamelCase : jnp.dtype =jnp.floataa
def __a ( self ) -> ... | 31 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
a : Tuple = logging.get_logger(__name__)
class __UpperCamelCase ( a__ ):
def __init__( self , *lower... | 710 |
"""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/lic... | 31 | 0 |
"""simple docstring"""
a : Tuple = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '... | 711 |
"""simple docstring"""
a : str = 8.314_4598
def _SCREAMING_SNAKE_CASE ( _lowercase : float , _lowercase : float ) ->float:
'''simple docstring'''
if temperature < 0:
raise Exception("Temperature cannot be less than 0 ... | 31 | 0 |
"""simple docstring"""
import math
def _SCREAMING_SNAKE_CASE ( ) ->None:
'''simple docstring'''
a : Tuple = input("Enter message: " )
a : List[Any] = int(input(F"""Enter key [2-{len(_lowercase ) - 1}]: """ ) ... | 712 |
"""simple docstring"""
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation imp... | 31 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a : Tuple = ... | 713 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 200 ) ->int:
'''simple docstring'''
a : Dict = [1, 2, 5, 10, 20, 50, 100, 200]
a : Optional[Any] = [0] * (pence + 1)
a : List[Any] = 1 # base case: ... | 31 | 0 |
"""simple docstring"""
import cva
import numpy as np
class __UpperCamelCase :
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ ) -> Tuple:
if k in (0.04, 0.06):
a : int = k
a : Dict = ... | 714 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=a__ ):
lowerCamelCase : Optional[Any] =["""transformers""", """torch""", """note_seq"""]
def __init__( self , *lowerCAme... | 31 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Optional[Any] = logging.get_logger(__name__)
a : List[Any] = {
'''tanreinama/GPTSAN-2.8B-spout_is_uniform''': (
'''https://huggingface.co/tanreina... | 715 |
"""simple docstring"""
import qiskit
def _SCREAMING_SNAKE_CASE ( _lowercase : int , _lowercase : int ) ->qiskit.result.counts.Counts:
'''simple docstring'''
a : Union[str, Any] = qiskit.Aer.get_backend("aer_simulator" ... | 31 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
norm... | 716 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[int] , _lowercase : Optional[Any] , _lowercase : Union[str, Any] ) ->Dict:
'''... | 31 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : list , _lowercase : int , _lowercase : int = 0 , _lowercase : int = 0 ) ->int:
'''simple docstring'''
a : int = right or len(_lowercase ) - 1
if ... | 717 |
"""simple docstring"""
import baseaa
def _SCREAMING_SNAKE_CASE ( _lowercase : str ) ->bytes:
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def _SCREAMING_SNAKE_CASE ( _lowercase : ... | 31 | 0 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __UpperCamelCase ( a__ , unittest.TestCase ):
lowerCamelCase ... | 718 |
"""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_... | 31 | 0 |
import argparse
import os
from accelerate.test_utils import execute_subprocess_async
def _SCREAMING_SNAKE_CASE ( _lowercase : str=None ) ->Optional[Any]:
'''simple docstring'''
if subparsers is not None:
a : Dict = subparsers.add_pa... | 719 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequ... | 31 | 0 |
from scipy.stats import pearsonr
import datasets
a : Union[str, Any] = '''
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assum... | 720 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _SCREAMING_SNAKE_CASE ( _lowercase : List[str] ) ->int:
... | 31 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...tes... | 721 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_... | 31 | 0 |
"""simple docstring"""
a : str = 8.31_4462 # Unit - J mol-1 K-1
def _SCREAMING_SNAKE_CASE ( _lowercase : float , _lowercase : float , _lowercase : float ) ->float:
'''simple docstring'''
if moles < 0 or kelvin... | 700 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 10 , _lowercase : int = 1000 , _lowercase : bool = True ) ->int:
'''simple docstring'''
assert (
isinstance(_lowercase , _lowercase )
and isinst... | 31 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : list[list[int | float]] ) ->int:
'''simple docstring'''
a : List[Any] = len(_lowercase )
a : Dict = len(matrix[0] )
a : List[str] = min(_lowercase ... | 701 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available... | 31 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a : Optional[int] = {
'''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Gra... | 702 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[Any] ,... | 31 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int ) ->int:
'''simple docstring'''
assert isinstance(_lowercase , _lowercase ), F"""The input value of [n={number}] is not an integer"""
if number == 1:
return 2
elif num... | 703 |
"""simple docstring"""
# Copyright 2022 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/lic... | 31 | 0 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] , _lowercase : int , _lowercase : int , _lowercase : int ) ->None:
'''simple docstring'''
if (direction... | 704 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_senten... | 31 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int , _lowercase : int ) ->int:
'''simple docstring'''
return number | (1 << position)
def _SCREAMING_SNAKE_CASE ( _lowercase : int , _lowercase : i... | 705 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 31 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : str = logging.get_logger(__name__)
a : Dict = {
'''microsoft/git-base''': '''https://huggingface.co/mic... | 706 |
"""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 datase... | 31 | 0 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class __UpperCamelCase ... | 707 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from d... | 31 | 0 |
"""simple docstring"""
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
a : Any = logging.get_logger(__name__)
... | 708 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __UpperCamelCase ( unittest.TestCase ):
def __a ( self ) -> Optional[Any]:
a : Optional[int] = [
... | 31 | 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 ( _lowercase : List[str] ) ->int:
... | 709 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class __UpperCamelCase ( nn.Module ):
lowerCamelCase : int
lowerCamelCase : jnp.dtype =jnp.floataa
def __a ( self ) -> ... | 31 | 0 |
"""simple docstring"""
import math
import qiskit
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 1 , _lowercase : int = 1 , _lowercase : int = 1 ) ->qiskit.result.counts.Counts:
'''simple docstring'''
if (
isinstan... | 710 |
"""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/lic... | 31 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
fro... | 711 |
"""simple docstring"""
a : str = 8.314_4598
def _SCREAMING_SNAKE_CASE ( _lowercase : float , _lowercase : float ) ->float:
'''simple docstring'''
if temperature < 0:
raise Exception("Temperature cannot be less than 0 ... | 31 | 0 |
"""simple docstring"""
import operator as op
def _SCREAMING_SNAKE_CASE ( _lowercase : Union[str, Any] ) ->Any:
'''simple docstring'''
a : str = []
a : List[str] = lambda _lowercase , _lowercase : int(x / y ... | 712 |
"""simple docstring"""
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation imp... | 31 | 0 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] ):
'''simple docstring'''
a : Union[str, Any] = len(_lowercase ) // 2
# choose the middle 3 elements
a : int ... | 713 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 200 ) ->int:
'''simple docstring'''
a : Dict = [1, 2, 5, 10, 20, 50, 100, 200]
a : Optional[Any] = [0] * (pence + 1)
a : List[Any] = 1 # base case: ... | 31 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : Any ) ->Tuple:
'''simple docstring'''
a : Optional[int] = len(_lowercase )
for i in range(length - 1 ):
a : Tuple = i
for k in range(i + 1 , _lower... | 714 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=a__ ):
lowerCamelCase : Optional[Any] =["""transformers""", """torch""", """note_seq"""]
def __init__( self , *lowerCAme... | 31 | 0 |
"""simple docstring"""
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseToken... | 715 |
"""simple docstring"""
import qiskit
def _SCREAMING_SNAKE_CASE ( _lowercase : int , _lowercase : int ) ->qiskit.result.counts.Counts:
'''simple docstring'''
a : Union[str, Any] = qiskit.Aer.get_backend("aer_simulator" ... | 31 | 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
a : Any = {
# 1536-bit
5: {
... | 716 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[int] , _lowercase : Optional[Any] , _lowercase : Union[str, Any] ) ->Dict:
'''... | 31 | 0 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepie... | 717 |
"""simple docstring"""
import baseaa
def _SCREAMING_SNAKE_CASE ( _lowercase : str ) ->bytes:
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def _SCREAMING_SNAKE_CASE ( _lowercase : ... | 31 | 0 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
i... | 718 |
"""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_... | 31 | 0 |
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as... | 719 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequ... | 31 | 0 |
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=a__ ):
lowerCamelCase : Optional[Any] =["""transformers""", """torch""", """note_seq"""]
def __init__( self , *lowerCAmelCase__ , **lowerCAmelCas... | 720 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _SCREAMING_SNAKE_CASE ( _lowercase : List[str] ) ->int:
... | 31 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, ... | 721 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_... | 31 | 0 |
"""simple docstring"""
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class __UpperCamelCase ( a__ , unittest.TestCase ):
lowerCamelCase : ... | 700 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 10 , _lowercase : int = 1000 , _lowercase : bool = True ) ->int:
'''simple docstring'''
assert (
isinstance(_lowercase , _lowercase )
and isinst... | 31 | 0 |
"""simple docstring"""
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
... | 701 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available... | 31 | 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 datase... | 702 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[Any] ,... | 31 | 0 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
a : Union[str, Any] = {
'''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/ma... | 703 |
"""simple docstring"""
# Copyright 2022 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/lic... | 31 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 50 ) ->int:
'''simple docstring'''
a : Dict = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile... | 704 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_senten... | 31 | 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
a : Optional[int] = '''src/t... | 705 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 31 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sent... | 706 |
"""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 datase... | 31 | 0 |
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokeniz... | 707 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from d... | 31 | 0 |
"""simple docstring"""
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class __UpperCamelCase :
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> List[Any]:
if dst_... | 708 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __UpperCamelCase ( unittest.TestCase ):
def __a ( self ) -> Optional[Any]:
a : Optional[int] = [
... | 31 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class __UpperCamelCase ( nn.Module ):
lowerCamelCase : int
lowerCamelCase : jnp.dtype =jnp.floataa
def __a ( self ) -> Tupl... | 709 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class __UpperCamelCase ( nn.Module ):
lowerCamelCase : int
lowerCamelCase : jnp.dtype =jnp.floataa
def __a ( self ) -> ... | 31 | 0 |
"""simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a : List[Any]... | 710 |
"""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/lic... | 31 | 0 |
"""simple docstring"""
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requ... | 711 |
"""simple docstring"""
a : str = 8.314_4598
def _SCREAMING_SNAKE_CASE ( _lowercase : float , _lowercase : float ) ->float:
'''simple docstring'''
if temperature < 0:
raise Exception("Temperature cannot be less than 0 ... | 31 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
a : Union[str, Any] = logging.get_logger(__name__)
class __UpperCamelCase ( a__ ):
def __init__( self , ... | 712 |
"""simple docstring"""
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation imp... | 31 | 0 |
"""simple docstring"""
import os
def _SCREAMING_SNAKE_CASE ( _lowercase : List[Any] ):
'''simple docstring'''
a : List[str] = len(grid[0] )
a : Union[str, Any] = len(_lowercase )
a : str = 0
a ... | 713 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 200 ) ->int:
'''simple docstring'''
a : Dict = [1, 2, 5, 10, 20, 50, 100, 200]
a : Optional[Any] = [0] * (pence + 1)
a : List[Any] = 1 # base case: ... | 31 | 0 |
"""simple docstring"""
import random
def _SCREAMING_SNAKE_CASE ( _lowercase : list , _lowercase : Optional[Any] ) ->tuple:
'''simple docstring'''
a : List[Any] = [], [], []
for element in data:
if element < pivot:
... | 714 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=a__ ):
lowerCamelCase : Optional[Any] =["""transformers""", """torch""", """note_seq"""]
def __init__( self , *lowerCAme... | 31 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
... | 715 |
"""simple docstring"""
import qiskit
def _SCREAMING_SNAKE_CASE ( _lowercase : int , _lowercase : int ) ->qiskit.result.counts.Counts:
'''simple docstring'''
a : Union[str, Any] = qiskit.Aer.get_backend("aer_simulator" ... | 31 | 0 |
"""simple docstring"""
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Dict = logging.get_logger(__name__)
a : ... | 716 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[int] , _lowercase : Optional[Any] , _lowercase : Union[str, Any] ) ->Dict:
'''... | 31 | 0 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class __UpperCamelCase :
lowerCamelCase : Tuple =None
def __a ( self ) -> Dict:
... | 717 |
"""simple docstring"""
import baseaa
def _SCREAMING_SNAKE_CASE ( _lowercase : str ) ->bytes:
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def _SCREAMING_SNAKE_CASE ( _lowercase : ... | 31 | 0 |
"""simple docstring"""
import math
def _SCREAMING_SNAKE_CASE ( _lowercase : float , _lowercase : float ) ->float:
'''simple docstring'''
if initial_intensity < 0:
raise ValueError("The value of intensity cannot be negative" )
# ... | 718 |
"""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_... | 31 | 0 |
def _SCREAMING_SNAKE_CASE ( _lowercase : Union[str, Any] , _lowercase : List[str] , _lowercase : Union[str, Any] , _lowercase : List[str] , _lowercase : Union[str, Any] , _lowercase : Union[str, Any] ) ->int:
'''simple docstring'''... | 719 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequ... | 31 | 0 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
a : Union[str, Any] = logging.get_logger(__name__)
cl... | 720 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _SCREAMING_SNAKE_CASE ( _lowercase : List[str] ) ->int:
... | 31 | 0 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class __UpperCamelCase ( datasets.BeamBasedBuilder ):
... | 721 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_... | 31 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Union[str, Any] = logging.get_logge... | 700 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 10 , _lowercase : int = 1000 , _lowercase : bool = True ) ->int:
'''simple docstring'''
assert (
isinstance(_lowercase , _lowercase )
and isinst... | 31 | 0 |
"""simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
a : Tuple = [
# (stable-diffusion, HF Diffusers)
('''time_embed.0.weigh... | 701 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available... | 31 | 0 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCamelCase ( a__ ):
lowerCamelCase : List[Any] =["""image_processor""", """tokenizer"""]
lowerCam... | 702 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[Any] ,... | 31 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepa... | 703 |
"""simple docstring"""
# Copyright 2022 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/lic... | 31 | 0 |
"""simple docstring"""
a : List[str] = tuple[float, float, float]
a : Union[str, Any] = tuple[float, float, float]
def _SCREAMING_SNAKE_CASE ( _lowercase : Pointad , _lowercase : Pointad ) ->Vectorad:
'''simple docstring'... | 704 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_senten... | 31 | 0 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
... | 705 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 31 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import ceil, floor, sqrt
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 200_0000 ) ->int:
'''simple docstring'''
a : list[int] = [0]
a : int
for id... | 706 |
"""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 datase... | 31 | 0 |
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple , _lowercase : int , _lowercase : Optional[Any] , _lowercase : Tuple ) ->Optional[Any]:
'''simple docstring'''
if height >= 1:
move_tower(height - 1 , _lowercase , _lowercase ... | 707 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from d... | 31 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a : Optional[int] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDep... | 708 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __UpperCamelCase ( unittest.TestCase ):
def __a ( self ) -> Optional[Any]:
a : Optional[int] = [
... | 31 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Any = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __UpperCamel... | 709 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class __UpperCamelCase ( nn.Module ):
lowerCamelCase : int
lowerCamelCase : jnp.dtype =jnp.floataa
def __a ( self ) -> ... | 31 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from d... | 710 |
"""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/lic... | 31 | 0 |
"""simple docstring"""
from pathlib import Path
import fire
def _SCREAMING_SNAKE_CASE ( _lowercase : str , _lowercase : str , _lowercase : int ) ->List[str]:
'''simple docstring'''
a : List[Any] = Path(_lowerc... | 711 |
"""simple docstring"""
a : str = 8.314_4598
def _SCREAMING_SNAKE_CASE ( _lowercase : float , _lowercase : float ) ->float:
'''simple docstring'''
if temperature < 0:
raise Exception("Temperature cannot be less than 0 ... | 31 | 0 |
"""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_pr... | 712 |
"""simple docstring"""
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation imp... | 31 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, r... | 713 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 200 ) ->int:
'''simple docstring'''
a : Dict = [1, 2, 5, 10, 20, 50, 100, 200]
a : Optional[Any] = [0] * (pence + 1)
a : List[Any] = 1 # base case: ... | 31 | 0 |
"""simple docstring"""
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class __UpperCamelCase ( a__ ):
lowerCamelCase : int ="""M-CLIP"""
def __init__( self , lowerCAmelCase__=1024 , ... | 714 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=a__ ):
lowerCamelCase : Optional[Any] =["""transformers""", """torch""", """note_seq"""]
def __init__( self , *lowerCAme... | 31 | 0 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase ( a__ ):
lowerCamelCase : Tuple =(KDPMaDiscreteScheduler,)
... | 715 |
"""simple docstring"""
import qiskit
def _SCREAMING_SNAKE_CASE ( _lowercase : int , _lowercase : int ) ->qiskit.result.counts.Counts:
'''simple docstring'''
a : Union[str, Any] = qiskit.Aer.get_backend("aer_simulator" ... | 31 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : List[Any] = {'''configuration_mmbt''': ['''MMBTConfig''']}
try:
if not is_torch_available():
raise OptionalDependencyNotAva... | 716 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[int] , _lowercase : Optional[Any] , _lowercase : Union[str, Any] ) ->Dict:
'''... | 31 | 0 |
"""simple docstring"""
import numpy as np
def _SCREAMING_SNAKE_CASE ( _lowercase : np.array ) ->np.array:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.tes... | 717 |
"""simple docstring"""
import baseaa
def _SCREAMING_SNAKE_CASE ( _lowercase : str ) ->bytes:
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def _SCREAMING_SNAKE_CASE ( _lowercase : ... | 31 | 0 |
"""simple docstring"""
import baseaa
def _SCREAMING_SNAKE_CASE ( _lowercase : str ) ->bytes:
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def _SCREAMING_SNAKE_CASE ( _lowercase : bytes ... | 718 |
"""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_... | 31 | 0 |
from collections.abc import Sequence
from queue import Queue
class __UpperCamelCase :
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__=None , lowerCAmelCase__=None ) -> Optional[int]:... | 719 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequ... | 31 | 0 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class __UpperCamelCase :
def __init__( self , lowerCAmelCase__=2 , lowerCAmelCase__=3 , lowerCAmelCase__=64 , ... | 720 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _SCREAMING_SNAKE_CASE ( _lowercase : List[str] ) ->int:
... | 31 | 0 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequ... | 721 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_... | 31 | 0 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def UpperCAmelCase__ ( UpperCAmelCase__ :List[Any] ):
'''simple docstring'''
if not is_accelerate_available():
return method
a ... | 32 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(UpperCAmelCase__ ), '''... | 32 | 1 |
import heapq
import sys
import numpy as np
A_ : List[str] = tuple[int, int]
class _lowercase :
def __init__( self : Any ) -> Tuple:
"""simple docstring"""
a = []
a = set()
def A ( sel... | 32 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : Any = logging.get_logger(__name__)
A_ : Optional[int] = {
'''SCUT-DLVCLab/lilt-roberta-en-base''': (
'''https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/ma... | 32 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
... | 32 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__ ( UpperCAmelCase__ :Optional[int] , UpperCAmelCase__ :List[str] , UpperCAmelCase__ :Any ... | 32 | 1 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
A_ : List[Any] = TypeVar('''T''')
A_ : int = Union[List[T], Tuple[T, ...]]
A_ : Tuple = Union[T, List[T], Dict[str, T]]
A_ : int = Union[str, bytes, os.PathLike]
| 32 |
def UpperCAmelCase__ ( UpperCAmelCase__ :int , UpperCAmelCase__ :int ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive" )
a = str(bin(UpperCAmelCase__ ) )[2:] # remove the leading "0b"
a ... | 32 | 1 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _lowercase ( UpperCAmelCase__ ):
_UpperCAmelCase = (EulerDiscreteScheduler,)
_UpperCAmelCase = 10
def A ... | 32 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
A_ : List[str] = (3, 9, -11, 0, 7, 5, 1, -1)
A_ : Optional[int] = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class _lowercase :
_UpperCAmelCase ... | 32 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : Tuple = logging.get_logger(__name__)
A_ : str = {
'''bert-base-uncased''': '''htt... | 32 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDepend... | 32 | 1 |
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from fla... | 32 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A_ : int = logging.get_logger(__name__)
A_ : str = {
'''microsoft/focalnet-tiny''': ... | 32 | 1 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepi... | 32 |
def UpperCAmelCase__ ( UpperCAmelCase__ :Any ):
'''simple docstring'''
if not head:
return True
# split the list to two parts
a , a = head.next, head
while fast and fast.next:
a = fast.next.next
a = slow.next
a = slow.next
a = N... | 32 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : Any = logging.get_logger(__name__)
A_ : Dict = {
'''studio-ousia/luke-base''': '''https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json''',
'''studio-ousia/lu... | 32 |
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ..... | 32 | 1 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def UpperCAmelCase__ ( UpperCAmelCase__ :dict ):
... | 32 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class _lowercase ( UpperCAmelCase__ ):
def A ( self : Optional[int] , __lowerCAmelCase : str ) -> Union[str, Any]:
"""s... | 32 | 1 |
from __future__ import annotations
from math import pow, sqrt
def UpperCAmelCase__ ( UpperCAmelCase__ :float , UpperCAmelCase__ :float , UpperCAmelCase__ :float ):
'''simple docstring'''
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueErro... | 32 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : Optional[int] = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''... | 32 | 1 |
def UpperCAmelCase__ ( UpperCAmelCase__ :list ):
'''simple docstring'''
a = len(UpperCAmelCase__ )
for i in range(1 , UpperCAmelCase__ ):
a = collection[i]
a = 0
a = i - 1
while low <= high:
a = (low + high) // 2
... | 32 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _lowercase ( UpperCAmelCase__ ):
_UpperCAmel... | 32 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : str = logging.get_logger(__name__)
A_ : List[Any] = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-... | 32 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, tor... | 32 | 1 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common ... | 32 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class _lowercase :
def __init__( self : List[str] ) -> List[str]:
"""simple docstring"""
a = ""
a = ""
a = []
a ... | 32 | 1 |
import argparse
import os
import re
A_ : Tuple = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
A_ : List[Any] = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
A_ : str = re.compile(r'''^... | 32 |
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 _lowercase ( UpperCAmelCase__ ):
_... | 32 | 1 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from... | 32 |
A_ : Any = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A_ : Tuple = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A_ : Optional[int] = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''Thursday''',
5: '''Friday''',
... | 32 | 1 |
def UpperCAmelCase__ ( UpperCAmelCase__ :int ):
'''simple docstring'''
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError("only integers accepted as input" )
else:
a = str(abs(UpperCAmelCase__ ) )
a = [list(UpperCA... | 32 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner im... | 32 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : Dict = logging.get_logger(__name__)
A_ : Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class _lowercase ( UpperCAm... | 32 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : str = logging.get_logger(__name__)
A_ : List[Any] = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-... | 32 | 1 |
from numpy import exp, pi, sqrt
def UpperCAmelCase__ ( UpperCAmelCase__ :str , UpperCAmelCase__ :float = 0.0 , UpperCAmelCase__ :float = 1.0 ):
'''simple docstring'''
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __nam... | 32 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
A_ : List... | 32 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase__ )
class _lowercase ( UpperCAmelCase__ ):
_UpperCAmelCase = field(default='''aut... | 32 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision... | 32 | 1 |
A_ : List[Any] = [
(10_00, '''M'''),
(9_00, '''CM'''),
(5_00, '''D'''),
(4_00, '''CD'''),
(1_00, '''C'''),
(90, '''XC'''),
(50, '''L'''),
(40, '''XL'''),
(10, '''X'''),
(9, '''IX'''),
(5, '''V'''),
(4, '''IV'''),
(1, '''I'''),
]
... | 32 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class _lowercase ( unittest.TestCase ):
de... | 32 | 1 |
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