code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lic... | 81 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase_ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 345 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A__ = {
"""configuration_funnel""": ["""FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FunnelConfig"""],
"""con... | 82 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRCont... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase__ :
lowercase__ = 42
lowercase__ = 42
class lowercase__ :
def __init__( self ... | 83 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.te... | 345 | 0 |
"""simple docstring"""
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbos... | 84 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class _snake_case ( __snake_case ):
'''simple docstring'''
A__ : str ... | 345 | 0 |
'''simple docstring'''
def UpperCamelCase_( snake_case : str ):
'''simple docstring'''
return credit_card_number.startswith(("34", "35", "37", "4", "5", "6") )
def UpperCamelCase_( snake_case : str ):
'''simple docstring'''
... | 85 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 345 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 86 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCamelCase_ ( _a : List[Any] ):
'''simple docstring'''
UpperCAmelCase_ : Optional[int] = [
"""decoder.version""",
... | 345 | 0 |
from __future__ import annotations
def lowercase_ ( _lowerCamelCase : list[int]):
return len(set(_lowerCamelCase)) == len(_lowerCamelCase)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 87 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTes... | 345 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import ena... | 88 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTe... | 345 | 0 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import ... | 89 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
UpperC... | 345 | 0 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowerCamelCase_ ( UpperCamelCase__ : dict ... | 90 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_safe... | 345 | 0 |
"""simple docstring"""
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,... | 91 |
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 ...test_model... | 345 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
logg... | 92 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _snake_case ( unittest.TestCase ):
'''simple docstring'''
def A__... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : int = {
"naver-clova-ix/donut-base": "https://huggingface.co/naver-clova-ix/donut-base/res... | 93 |
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_tensor
if is_torch_availabl... | 345 | 0 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
if dst_width < 0 or dst_height < 0:
raise ValueError('''Destination width/height should b... | 94 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
clas... | 345 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : List[str] = {
"""configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TimesformerConfig"""],
}
try:
if not i... | 95 |
def lowerCamelCase_ ( _a : List[str] ):
'''simple docstring'''
UpperCAmelCase_ : Tuple = [0] * len(_a )
UpperCAmelCase_ : Dict = []
UpperCAmelCase_ : Optional[int] = []
UpperCAmelCase_ : Dict = 0
for values in graph.values... | 345 | 0 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor,... | 96 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/ma... | 345 | 0 |
'''simple docstring'''
def a ( __a , __a , __a , __a ) -> str:
'''simple docstring'''
if height >= 1:
move_tower(height - 1 , __a , __a , __a )
move_disk(__a , __a )
move_tower(height - 1 , __a , __a , __a )
... | 97 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 345 | 0 |
"""simple docstring"""
from __future__ import annotations
import queue
class snake_case :
"""simple docstring"""
def __init__( self : int ,lowerCamelCase__ : List[str] ):
UpperCAmelCase__ = data
UpperCAmelCase__ = None
... | 98 |
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=__snake_case ):
'''simple docstring'''
A__ : Tuple = ["flax"]
def __init__( self: str ,*lowerCamelCase_: int ,**lowerCamelCase_: List[str] ) -> str:
requires... | 345 | 0 |
lowercase : List[Any] = 2_5_6
# Modulus to hash a string
lowercase : Any = 1_0_0_0_0_0_3
def A_ ( A__ , A__ ) -> bool:
a__ : List[str] = len(A__ )
a__ : List[Any] = len(A__ )
if p_len > t_len:
return Fa... | 99 |
import random
from typing import Any
def lowerCamelCase_ ( _a : list ):
'''simple docstring'''
for _ in range(len(_a ) ):
UpperCAmelCase_ : Tuple = random.randint(0 , len(_a ) - 1 )
UpperCAmelCase_ : List[Any] = random.randint(0 ... | 345 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
"configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}
try:
if not is_torch_available():
... | 100 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _snake_case ( nn.Module ):
'''simple docstring'''
A__ : int
A__ : int
A__ : ... | 345 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import ... | 101 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _snake_case :
'''simple docstring'''
def __init__( self: Any ,lowerCamelCase_: Dict ,lowerCamelCase_: Tuple ,lowerCamelCase_: Dict ,lowerCamelCase_: Tuple ,lowerCamelCase_: Any ,lowe... | 345 | 0 |
"""simple docstring"""
def lowercase ( ) ->List[Any]:
"""simple docstring"""
__snake_case : int = 0
for i in range(1 , 1_001 ):
total += i**i
return str(_snake_case )[-10:]
if __name__ == "__main__":
print(solution())
| 102 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _snake_case ( __snake_case , unittest.TestCase ):
'''simple docstring'''
A... | 345 | 0 |
from heapq import heappop, heappush
import numpy as np
def UpperCamelCase( __UpperCamelCase : np.ndarray ,__UpperCamelCase : tuple[int, int] ,__UpperCamelCase : tuple[int, int] ,__UpperCamelCase : bool ,):
lowerCAmelCase_ , lowerCAmelCase_ : Optional[i... | 103 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase_ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 345 | 0 |
'''simple docstring'''
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 _A ( A__ ):
"""simple docstri... | 104 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRCont... | 345 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
a : str = logging.get... | 105 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.te... | 345 | 0 |
"""simple docstring"""
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
__UpperCamelCase : Tuple = TypeVar('''T''')
class SCREAMING_SNAKE_CASE ( Generic[T] ):
"""simple docstring"""
lowerc... | 106 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class _snake_case ( __snake_case ):
'''simple docstring'''
A__ : str ... | 345 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... | 107 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 345 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=lowercase ):
"""simple docstring"""
a : str =["transformers", "torch", "note_seq"]
def __init__( self , *snake_case__ , **snake_case__ ... | 108 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCamelCase_ ( _a : List[Any] ):
'''simple docstring'''
UpperCAmelCase_ : Optional[int] = [
"""decoder.version""",
... | 345 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
A: List[str] = logging.get_logger(__name__... | 109 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTes... | 345 | 0 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __A ( pl.LightningModule ):
def __init__(self : str , __a : int ):
super().__init_... | 1 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTe... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A =logging.get_logger(__name__)
A ={
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json',
}
class _a ( __snake_case ):
... | 34 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
UpperC... | 345 | 0 |
'''simple docstring'''
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
_lowercase : Dict = logging.getLogger(__name__)
if is_torch_t... | 239 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_safe... | 345 | 0 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenizer,... | 192 |
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 ...test_model... | 345 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 20 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _snake_case ( unittest.TestCase ):
'''simple docstring'''
def A__... | 345 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import lo... | 268 |
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_tensor
if is_torch_availabl... | 345 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
'''configuration_roformer''': ['''ROFORMER_PRETRAINED_... | 283 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
clas... | 345 | 0 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
_SCREAMING_SNAKE_CASE = transforms... | 343 |
def lowerCamelCase_ ( _a : List[str] ):
'''simple docstring'''
UpperCAmelCase_ : Tuple = [0] * len(_a )
UpperCAmelCase_ : Dict = []
UpperCAmelCase_ : Optional[int] = []
UpperCAmelCase_ : Dict = 0
for values in graph.values... | 345 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
A__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class a ( __snake_case ):
... | 230 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/ma... | 345 | 0 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTest... | 344 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 345 | 0 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( __snake_case : list[int | float] , __snake_case : int , __snake_case : int ):
'''simple docstring'''
if len(_a ) == 0:
raise ValueError('find_max() arg is an empty sequence... | 220 |
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=__snake_case ):
'''simple docstring'''
A__ : Tuple = ["flax"]
def __init__( self: str ,*lowerCamelCase_: int ,**lowerCamelCase_: List[str] ) -> str:
requires... | 345 | 0 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class __A :
def __init__(self : Any , __a : Dict , __a : Tuple , __a : Dict , __a : Tuple , __a : Any , __a : Tuple=0.2 , __a ... | 1 |
import random
from typing import Any
def lowerCamelCase_ ( _a : list ):
'''simple docstring'''
for _ in range(len(_a ) ):
UpperCAmelCase_ : Tuple = random.randint(0 , len(_a ) - 1 )
UpperCAmelCase_ : List[Any] = random.randint(0 ... | 345 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _a ( metaclass=__snake_case ):
__a : Tuple = ["flax"]
def __init__( self : str , *lowercase : int , **lowercase : List[str] ):
'''simple docstring'''... | 34 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _snake_case ( nn.Module ):
'''simple docstring'''
A__ : int
A__ : int
A__ : ... | 345 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int ) -> Union[str, Any]:
if num <= 0:
raise ValueError("""Input must be a positive integer""" )
lowercase_ : Union[str, Any] = [True] * (num + 1)
lowercase_ ... | 239 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _snake_case :
'''simple docstring'''
def __init__( self: Any ,lowerCamelCase_: Dict ,lowerCamelCase_: Tuple ,lowerCamelCase_: Dict ,lowerCamelCase_: Tuple ,lowerCamelCase_: Any ,lowe... | 345 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface import HuggingFace
... | 192 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _snake_case ( __snake_case , unittest.TestCase ):
'''simple docstring'''
A... | 345 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> List[Any]:
lowercase : Tuple = [0] * len(_a )
lowercase : Dict = []
lowercase : Optional[int] = []
lowercase : Dict = 0
for values in ... | 20 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase_ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 345 | 0 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/m... | 268 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRCont... | 345 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/c... | 283 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.te... | 345 | 0 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.test_... | 343 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class _snake_case ( __snake_case ):
'''simple docstring'''
A__ : str ... | 345 | 0 |
from ..utils import DummyObject, requires_backends
class a ( metaclass=__snake_case ):
__lowerCAmelCase : List[str] = ["torch"]
def __init__( self :Optional[int] ,*__lowercase :Tuple ,**__lowercase :Tuple ):
requires_backends(self ... | 230 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 345 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _lowerCAmelCase ( unittest.TestCase, __snake_case ):
"""simple docstring"""
def UpperCAmelCase_ ( self ) -> Tuple:
A_ : ... | 344 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCamelCase_ ( _a : List[Any] ):
'''simple docstring'''
UpperCAmelCase_ : Optional[int] = [
"""decoder.version""",
... | 345 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCamelCase : Union[str, Any] = {
'configuration_resnet': ['RESNET_PRETRAINED_CONFIG_ARCH... | 220 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTes... | 345 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 1 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTe... | 345 | 0 |
'''simple docstring'''
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _a ( __snake_case ):
def __init__( self : Tuple , lowercase : int , lowercase : Union[... | 34 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
UpperC... | 345 | 0 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Any:
def wrapper(*UpperCAmelCase__ : Tuple ... | 239 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_safe... | 345 | 0 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingface... | 192 |
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 ...test_model... | 345 | 0 |
from math import pi, sqrt
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> List[Any]:
if num <= 0:
raise ValueError("""math domain error""" )
if num > 171.5:
raise OverflowError("""math range error""" )
elif num - int(_a ) not in (0, 0.5):
... | 20 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _snake_case ( unittest.TestCase ):
'''simple docstring'''
def A__... | 345 | 0 |
"""simple docstring"""
from collections.abc import Callable
def snake_case ( A__ ,A__ ,A__ ):
UpperCAmelCase_ : float = a
UpperCAmelCase_ : float = b
if function(_a ) == 0: # one of the a or b is a root for the function
return a
elif function... | 268 |
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_tensor
if is_torch_availabl... | 345 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
lo... | 283 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
clas... | 345 | 0 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_SCREAMING... | 343 |
def lowerCamelCase_ ( _a : List[str] ):
'''simple docstring'''
UpperCAmelCase_ : Tuple = [0] * len(_a )
UpperCAmelCase_ : Dict = []
UpperCAmelCase_ : Optional[int] = []
UpperCAmelCase_ : Dict = 0
for values in graph.values... | 345 | 0 |
import math
def _lowerCAmelCase ( __lowerCAmelCase ) -> List[str]:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers,... | 230 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/ma... | 345 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNet... | 344 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 345 | 0 |
"""simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class a :
def __init__( self , _lowerCamelCase ):
if isinstance(lowerCamelCase_ ... | 220 |
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=__snake_case ):
'''simple docstring'''
A__ : Tuple = ["flax"]
def __init__( self: str ,*lowerCamelCase_: int ,**lowerCamelCase_: List[str] ) -> str:
requires... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_: int =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_: str ={
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'tiiuae/falco... | 1 |
import random
from typing import Any
def lowerCamelCase_ ( _a : list ):
'''simple docstring'''
for _ in range(len(_a ) ):
UpperCAmelCase_ : Tuple = random.randint(0 , len(_a ) - 1 )
UpperCAmelCase_ : List[Any] = random.randint(0 ... | 345 | 0 |
'''simple docstring'''
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
A =logging.get_logger(__nam... | 34 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _snake_case ( nn.Module ):
'''simple docstring'''
A__ : int
A__ : int
A__ : ... | 345 | 0 |
'''simple docstring'''
# Imports
import numpy as np
class __magic_name__ :
def __init__( self : Union[str, Any] , lowercase_ : Dict=None , lowercase_ : Dict=None , lowercase_ : Optional[Any]=None , lowercase_ : Union[str, Any]=None , lowercase_ ... | 239 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _snake_case :
'''simple docstring'''
def __init__( self: Any ,lowerCamelCase_: Dict ,lowerCamelCase_: Tuple ,lowerCamelCase_: Dict ,lowerCamelCase_: Tuple ,lowerCamelCase_: Any ,lowe... | 345 | 0 |
def UpperCamelCase (lowercase_: list[list[int]] , lowercase_: int , lowercase_: int , lowercase_: list[int] ) -> Optional[Any]:
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Validate that next vertex is not already in path
return not any(vertex... | 192 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _snake_case ( __snake_case , unittest.TestCase ):
'''simple docstring'''
A... | 345 | 0 |
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, slow, torch_... | 20 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase_ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 345 | 0 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def snake_case ( A__ ,... | 268 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRCont... | 345 | 0 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : List[str] = 0
# if input_string is "aba" than new_input_string become "a|b|a"
lowerCamelCase : Union[str, Any] = """"""
lowerCamelCase : str = """"""
# append each characte... | 283 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.te... | 345 | 0 |
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, is_vision_available
from ..... | 343 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class _snake_case ( __snake_case ):
'''simple docstring'''
A__ : str ... | 345 | 0 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
A__ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 230 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 345 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
'Bridg... | 344 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCamelCase_ ( _a : List[Any] ):
'''simple docstring'''
UpperCAmelCase_ : Optional[int] = [
"""decoder.version""",
... | 345 | 0 |
"""simple docstring"""
from itertools import product
def _SCREAMING_SNAKE_CASE ( __snake_case : int , __snake_case : int ):
'''simple docstring'''
lowercase = sides_number
lowercase = max_face_number * dice_number
lowercase = ... | 220 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTes... | 345 | 0 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def lowerCAmelCase_ ( snake_case_ : Any ) -> List[str]:
'''simple docstring'''
... | 1 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTe... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def snake_case_ (_a : str , _a : float | Decimal , _a : float = 1_0**-1_0 ):
UpperCAmelCase = a
w... | 34 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
UpperC... | 345 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Tuple = logging.get_logger(__name__)
_lowercase : int = {"vocab_file": "vocab.json"}
_lowercase : Tu... | 239 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_safe... | 345 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : str = logging.get_logger(__name__)
A_ : str = {
'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
# See all CANINE models at https://huggingface.co/model... | 192 |
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 ...test_model... | 345 | 0 |
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,
to_channel_dimension_forma... | 20 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _snake_case ( unittest.TestCase ):
'''simple docstring'''
def A__... | 345 | 0 |
"""simple docstring"""
class UpperCamelCase_ :
def __init__( self : int , lowerCAmelCase_ : int ) -> int:
UpperCAmelCase_ : Tuple = n
UpperCAmelCase_ : Tuple = [None] * self.n
UpperCAmelCase_ : Optional[int] = 0 # i... | 268 |
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_tensor
if is_torch_availabl... | 345 | 0 |
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,
... | 283 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
clas... | 345 | 0 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavin... | 343 |
def lowerCamelCase_ ( _a : List[str] ):
'''simple docstring'''
UpperCAmelCase_ : Tuple = [0] * len(_a )
UpperCAmelCase_ : Dict = []
UpperCAmelCase_ : Optional[int] = []
UpperCAmelCase_ : Dict = 0
for values in graph.values... | 345 | 0 |
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_accelerate_available,
... | 230 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/ma... | 345 | 0 |
'''simple docstring'''
UpperCamelCase__ : Optional[int] = '0.18.2'
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_a... | 344 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 345 | 0 |
"""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 t... | 220 |
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=__snake_case ):
'''simple docstring'''
A__ : Tuple = ["flax"]
def __init__( self: str ,*lowerCamelCase_: int ,**lowerCamelCase_: List[str] ) -> str:
requires... | 345 | 0 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE_: Tuple =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_: List[str] ={
'google/umt5-small': 'htt... | 1 |
import random
from typing import Any
def lowerCamelCase_ ( _a : list ):
'''simple docstring'''
for _ in range(len(_a ) ):
UpperCAmelCase_ : Tuple = random.randint(0 , len(_a ) - 1 )
UpperCAmelCase_ : List[Any] = random.randint(0 ... | 345 | 0 |
'''simple docstring'''
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
A =[
'word_embeddings_layernorm.... | 34 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _snake_case ( nn.Module ):
'''simple docstring'''
A__ : int
A__ : int
A__ : ... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list ) -> Union[str, Any]:
if not nums:
raise ValueError("""List is empty""" )
return sum(_a ) / len(_a )
if __name__ == "__main__":
import docte... | 239 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _snake_case :
'''simple docstring'''
def __init__( self: Any ,lowerCamelCase_: Dict ,lowerCamelCase_: Tuple ,lowerCamelCase_: Dict ,lowerCamelCase_: Tuple ,lowerCamelCase_: Any ,lowe... | 345 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 192 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _snake_case ( __snake_case , unittest.TestCase ):
'''simple docstring'''
A... | 345 | 0 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __snake_case ( __snake_case , unittest.TestCase ):
_a : Optional[Any]= CTRLTokenizer
_a : ... | 20 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase_ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 345 | 0 |
"""simple docstring"""
from math import pow
def snake_case ( A__ ,A__ ,A__ ,A__ ,A__ ,):
if current_sum == needed_sum:
# If the sum of the powers is equal to needed_sum, then we have a solution.
solutions_count += 1
return current_sum, solutions_count
UpperCAmelCase_ ... | 268 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRCont... | 345 | 0 |
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common ... | 283 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.te... | 345 | 0 |
def lowercase( UpperCamelCase_ , UpperCamelCase_ = 0 ) -> int:
'''simple docstring'''
UpperCamelCase = length or len(_a )
UpperCamelCase = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
UpperCamelCase = list_data[i + 1], ... | 343 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class _snake_case ( __snake_case ):
'''simple docstring'''
A__ : str ... | 345 | 0 |
import numpy as np
def _lowerCAmelCase ( __lowerCAmelCase ) -> Any:
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 230 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMi... | 344 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCamelCase_ ( _a : List[Any] ):
'''simple docstring'''
UpperCAmelCase_ : Optional[int] = [
"""decoder.version""",
... | 345 | 0 |
"""simple docstring"""
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_UpperCamelCase : Optional[int] ... | 220 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTes... | 345 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import gcd
def lowerCAmelCase_ ( snake_case_ : int , snake_case_ : int = 2 , snake_case_ : int = 1 , snake_case_ : int = 3 , ) -> Dict:
'''simple docstring'''
... | 1 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTe... | 345 | 0 |
'''simple docstring'''
import math
def snake_case_ (_a : list , _a : int ):
UpperCAmelCase = len(_a )
UpperCAmelCase = int(math.floor(math.sqrt(_a ) ) )
UpperCAmelCase = 0
while arr[min(_a , _a ) - 1... | 34 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
UpperC... | 345 | 0 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
... | 239 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_safe... | 345 | 0 |
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 ...utils import logging
fr... | 192 |
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 ...test_model... | 345 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 20 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _snake_case ( unittest.TestCase ):
'''simple docstring'''
def A__... | 345 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.