code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase_ ( tf.keras.layers.... | 334 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> str | Literal[False]:
A: List[str] = list(__lowercase )
A: ... | 334 | 1 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_confi... | 334 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> Tuple:
A: Tuple = len(__lowercase )
for i in range(length - 1 ):
A: Dict = i
for k in range(i + 1 , __lowercase ):
... | 334 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jn... | 334 |
'''simple docstring'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : List[str] ) -> ... | 334 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
'''configuration_convnext''': ['''CONVNEXT_PRETRAINED_C... | 334 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Padd... | 334 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,... | 334 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import Tokeniz... | 334 | 1 |
'''simple docstring'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : List[str] ) -> ... | 334 |
'''simple docstring'''
import requests
UpperCamelCase = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def SCREAMING_SNAKE_CASE( __lowercase ) -> None:
# fetching a list of articles in json format
A: Tuple = requests.get(_NE... | 334 | 1 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
... | 334 |
'''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_availa... | 334 | 1 |
'''simple docstring'''
# Copyright 2023 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/... | 334 |
'''simple docstring'''
import os
from distutils.util import strtobool
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> List[Any]:
for e in env_keys:
A: Dict = int(os.environ.get(__lowercase , -1 ) )
if val ... | 334 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 334 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/f... | 334 | 1 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
... | 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEnc... | 334 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''SCUT-DLVCLab/lilt-roberta-en-base''': (
'''https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en... | 334 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> list[list[float]]:
A: list[list[float]] = []
for data in source_data:
for i, el in enumerate(__lowercase ):
if len(__lowercase ) < i + 1:
da... | 334 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> str:
A: Optional[int] = 0
A: Dict = len(__lowercase )
for i in range(n - 1 ):
for j in range(i + 1 , __lowercase ):
i... | 334 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_... | 334 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbed... | 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDep... | 334 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> list:
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError('''The given input must be positive''' )
# get the generated string sequence
A: Optional... | 334 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
pass
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( ... | 334 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def SCREAMING_SNAKE_CASE( __lowercase ) -> Optional[int]:
A: Tuple = SwinConfig(image_... | 334 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase = 4 ) -> list[list[int]]:
A: Tuple = abs(__lowercase ) or 4
return [[1 + x + y * row_size for x in range(__lowercase )] for y in range(__lowercase )]
de... | 334 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm imp... | 334 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def SCREAMING_SNAKE_CASE( __lowercase ) -> Dict:
return np.maximum(0 , __lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 334 | 1 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo... | 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_speec... | 334 | 1 |
'''simple docstring'''
import math
import sys
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if number != int(__lowercase ):
raise ValueError('''the value of input must be a natural number''' )
if number < 0:
raise ValueError('''the value of input mu... | 334 |
'''simple docstring'''
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import Mode... | 334 | 1 |
'''simple docstring'''
import requests
UpperCamelCase = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def SCREAMING_SNAKE_CASE( __lowercase ) -> None:
# fetching a list of articles in json format
A: Tuple = requests.get(_NE... | 334 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbed... | 334 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_ima... | 334 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
... | 334 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.... | 334 |
'''simple docstring'''
from collections import deque
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNA... | 334 | 1 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_ut... | 334 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
fro... | 334 | 1 |
'''simple docstring'''
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.s... | 334 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> str | Literal[False]:
A: List[str] = list(__lowercase )
A: ... | 334 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase = 0 , __lowercase = 0 ) -> int:
A: Union[str, Any] = right or len(__lowercase ) - 1
if left > right:
return -1
elif lis... | 334 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> Tuple:
A: Tuple = len(__lowercase )
for i in range(length - 1 ):
A: Dict = i
for k in range(i + 1 , __lowercase ):
... | 334 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
UpperCamelCase_ : int = ["""image_pr... | 334 |
'''simple docstring'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : List[str] ) -> ... | 334 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> list:
if len(__lowercase ) <= 1:
return [tuple(__lowercase )]
A: Any = []
def generate(__lowercase , __lowercase ):
A: Union[str, Any]... | 334 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Padd... | 334 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> Optional[Any]:
A: Optional[Any] = [0] * len(__lowercase )
A: Any = []
A: Any = [1] * len(__lowercase )
for values in graph.values():... | 334 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import Tokeniz... | 334 | 1 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class lowerCAmelCase_ ( logging.LoggerAdapter ):
'''simple docstring'''
@staticmethod
def _snake_case ( SCREAMING_SNAKE_CASE_ : Optional[int] ) -> ... | 334 |
'''simple docstring'''
import requests
UpperCamelCase = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def SCREAMING_SNAKE_CASE( __lowercase ) -> None:
# fetching a list of articles in json format
A: Tuple = requests.get(_NE... | 334 | 1 |
'''simple docstring'''
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
UpperCamelCase = ... | 334 |
'''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_availa... | 334 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowerCAmelCase_ :
'''simple docstring'''
UpperCamelCase_ : Optional[str] = field(
default="""codeparrot/codeparrot""" , metadata... | 334 |
'''simple docstring'''
import os
from distutils.util import strtobool
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> List[Any]:
for e in env_keys:
A: Dict = int(os.environ.get(__lowercase , -1 ) )
if val ... | 334 | 1 |
'''simple docstring'''
import numpy as np
import datasets
UpperCamelCase = '''
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the Euclidean dista... | 334 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/f... | 334 | 1 |
'''simple docstring'''
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
... | 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEnc... | 334 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, Levi... | 334 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> list[list[float]]:
A: list[list[float]] = []
for data in source_data:
for i, el in enumerate(__lowercase ):
if len(__lowercase ) < i + 1:
da... | 334 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/f... | 334 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_... | 334 | 1 |
'''simple docstring'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : str ) -> None:
'''simple docstring'''
A: dict[str, TrieNode] = {} # Mapping from char to TrieNode
A... | 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDep... | 334 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterM... | 334 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
pass
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( ... | 334 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel... | 334 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase = 4 ) -> list[list[int]]:
A: Tuple = abs(__lowercase ) or 4
return [[1 + x + y * row_size for x in range(__lowercase )] for y in range(__lowercase )]
de... | 334 | 1 |
'''simple docstring'''
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class lowerCAmelCase_ ( UpperCAmelCase... | 334 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def SCREAMING_SNAKE_CASE( __lowercase ) -> Dict:
return np.maximum(0 , __lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 334 | 1 |
'''simple docstring'''
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
UpperCamelCase = object()
# For specifying empty leaf dict `{}`
UpperCamelCase = ... | 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_speec... | 334 | 1 |
'''simple docstring'''
import warnings
from ..trainer import Trainer
from ..utils import logging
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __init__( self : ... | 334 |
'''simple docstring'''
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import Mode... | 334 | 1 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration... | 334 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbed... | 334 | 1 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from tran... | 334 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
... | 334 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
'''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2VecAudioCo... | 334 |
'''simple docstring'''
from collections import deque
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNA... | 334 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
UpperCamelCase = {
'''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''E... | 334 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
fro... | 334 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {'''vo... | 334 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> str | Literal[False]:
A: List[str] = list(__lowercase )
A: ... | 334 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list:
if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2:
raise Exception('''Matr... | 334 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> Tuple:
A: Tuple = len(__lowercase )
for i in range(length - 1 ):
A: Dict = i
for k in range(i + 1 , __lowercase ):
... | 334 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNe... | 334 |
'''simple docstring'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : List[str] ) -> ... | 334 | 1 |
'''simple docstring'''
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 i... | 334 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Padd... | 334 | 1 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
ex... | 334 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import Tokeniz... | 334 | 1 |
'''simple docstring'''
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBack... | 334 |
'''simple docstring'''
import requests
UpperCamelCase = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def SCREAMING_SNAKE_CASE( __lowercase ) -> None:
# fetching a list of articles in json format
A: Tuple = requests.get(_NE... | 334 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
pass
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( ... | 334 |
'''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_availa... | 334 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxConfi... | 334 |
'''simple docstring'''
import os
from distutils.util import strtobool
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> List[Any]:
for e in env_keys:
A: Dict = int(os.environ.get(__lowercase , -1 ) )
if val ... | 334 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''xlm-... | 334 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/f... | 334 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
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 ImageProcessingSav... | 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEnc... | 334 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_availa... | 334 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> list[list[float]]:
A: list[list[float]] = []
for data in source_data:
for i, el in enumerate(__lowercase ):
if len(__lowercase ) < i + 1:
da... | 334 | 1 |
'''simple docstring'''
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class lowerCAmelCase_ ( UpperCAmelCase_ ):
... | 334 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_... | 334 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def SCREAMING_SNAKE_CASE( __lowercase ) -> Dict:
return np.maximum(0 , __lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDep... | 334 | 1 |
'''simple docstring'''
from __future__ import annotations
from functools import lru_cache
from math import ceil
UpperCamelCase = 100
UpperCamelCase = set(range(3, NUM_PRIMES, 2))
primes.add(2)
UpperCamelCase = 42
for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
... | 334 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
pass
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( ... | 334 | 1 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with... | 334 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase = 4 ) -> list[list[int]]:
A: Tuple = abs(__lowercase ) or 4
return [[1 + x + y * row_size for x in range(__lowercase )] for y in range(__lowercase )]
de... | 334 | 1 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowerCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
def _snake_case ... | 334 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def SCREAMING_SNAKE_CASE( __lowercase ) -> Dict:
return np.maximum(0 , __lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 334 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> float:
if digit_amount > 0:
return round(number - int(__lowercase ) , __lowercase )
return number - int(__lowercase )
if __name__ == "__main__":
pr... | 334 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_speec... | 334 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_util... | 334 |
'''simple docstring'''
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import Mode... | 334 | 1 |
'''simple docstring'''
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def __init... | 334 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbed... | 334 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> str | Literal[False]:
A: List[str] = list(__lowercase )
A: ... | 334 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
... | 334 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {... | 334 |
'''simple docstring'''
from collections import deque
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNA... | 334 | 1 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_... | 334 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
fro... | 334 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase = 1_0_0_0 ) -> int:
A: int = -1
A: Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
... | 334 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> str | Literal[False]:
A: List[str] = list(__lowercase )
A: ... | 334 | 1 |
'''simple docstring'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , SCREAMING_SNAKE_CASE_ : list ) -> None:
'''simple docstring'''
A: Any = s... | 334 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> Tuple:
A: Tuple = len(__lowercase )
for i in range(length - 1 ):
A: Dict = i
for k in range(i + 1 , __lowercase ):
... | 334 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase = log... | 334 |
'''simple docstring'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : List[str] ) -> ... | 334 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase_ )
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simpl... | 334 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Padd... | 334 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Padd... | 334 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import Tokeniz... | 334 | 1 |
'''simple docstring'''
from __future__ import annotations
from cmath import sqrt
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> tuple[complex, complex]:
if a == 0:
raise ValueError('''Coefficient \'a\' must not be zero.''' ... | 350 |
'''simple docstring'''
import requests
UpperCamelCase = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def SCREAMING_SNAKE_CASE( __lowercase ) -> None:
# fetching a list of articles in json format
A: Tuple = requests.get(_NE... | 334 | 0 |
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> int:
return int((input_a, input_a).count(0 ) == 0 )
def SCREAMING_SNAKE_CASE( ) -> None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(... | 351 |
'''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_availa... | 334 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
'''configuration_mgp_str''': ['''MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MgpstrConfig'''],
'''processing_mgp_str''... | 352 |
'''simple docstring'''
import os
from distutils.util import strtobool
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> List[Any]:
for e in env_keys:
A: Dict = int(os.environ.get(__lowercase , -1 ) )
if val ... | 334 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCamelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 353 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/f... | 334 | 0 |
'''simple docstring'''
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 ... | 354 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEnc... | 334 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase : float , __lowercase : int ) -> int:
if digit_amount > 0:
return round(number - int(__a ) , __a )
return number - int(__a )
if __name__ == "__main__":
print(... | 355 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> list[list[float]]:
A: list[list[float]] = []
for data in source_data:
for i, el in enumerate(__lowercase ):
if len(__lowercase ) < i + 1:
da... | 334 | 0 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase__ ):
'''simple docstring'''
def __init__( self ... | 356 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_... | 334 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
"configuration_instructblip": [
"INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InstructBlipConfig",
... | 357 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDep... | 334 | 0 |
'''simple docstring'''
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def SCREAMING_SNAKE_CASE( __lowercase = "isbn/0140328726" ) -> Optional[Any]:
A: Tuple = olid.strip().strip('''/''' ) # Remove lead... | 358 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
pass
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( ... | 334 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase = {
"""configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfi... | 359 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase = 4 ) -> list[list[int]]:
A: Tuple = abs(__lowercase ) or 4
return [[1 + x + y * row_size for x in range(__lowercase )] for y in range(__lowercase )]
de... | 334 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
'''configuration_groupvit''': [
'''GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''GroupViTConfig''',
... | 360 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def SCREAMING_SNAKE_CASE( __lowercase ) -> Dict:
return np.maximum(0 , __lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 334 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {
'''configuration_vivit''': ['''VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VivitConfig'''],
}... | 361 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_speec... | 334 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_... | 362 |
'''simple docstring'''
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import Mode... | 334 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import pi
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> dict[str, float]:
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('''One... | 363 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbed... | 334 | 0 |
'''simple docstring'''
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from s... | 364 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
... | 334 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,... | 365 |
'''simple docstring'''
from collections import deque
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNA... | 334 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> int:
... | 366 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
fro... | 334 | 0 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'''files''' , [
['''full:README.md''', '''dataset_infos.json'''],... | 367 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> str | Literal[False]:
A: List[str] = list(__lowercase )
A: ... | 334 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class l... | 368 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> Tuple:
A: Tuple = len(__lowercase )
for i in range(length - 1 ):
A: Dict = i
for k in range(i + 1 , __lowercase ):
... | 334 | 0 |
'''simple docstring'''
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
UpperCamelCase = logging.get_logger(__name__)
de... | 369 |
'''simple docstring'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : List[str] ) -> ... | 334 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_commo... | 370 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Padd... | 334 | 0 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def SCREAMING_SNAKE_CASE( ) -> Dict:
with offline(OfflineSimulationMode.C... | 371 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import Tokeniz... | 334 | 0 |
'''simple docstring'''
UpperCamelCase = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
UpperCamelCase = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> List[Any]:
A: Op... | 350 |
'''simple docstring'''
import requests
UpperCamelCase = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def SCREAMING_SNAKE_CASE( __lowercase ) -> None:
# fetching a list of articles in json format
A: Tuple = requests.get(_NE... | 334 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow... | 351 |
'''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_availa... | 334 | 0 |
'''simple docstring'''
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowerCAmelCase_ :
'''simple docstring'''
UpperCamelCase_ : Optional[int] = None
def _snake_c... | 352 |
'''simple docstring'''
import os
from distutils.util import strtobool
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> List[Any]:
for e in env_keys:
A: Dict = int(os.environ.get(__lowercase , -1 ) )
if val ... | 334 | 0 |
'''simple docstring'''
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
UpperCamelCase = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE( __lowercase ) -> Tuple:
... | 353 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/f... | 334 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_roberta''': ... | 354 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEnc... | 334 | 0 |
'''simple docstring'''
import numpy as np
import qiskit
def SCREAMING_SNAKE_CASE( __lowercase : int = 8 , __lowercase : int | None = None ) -> str:
A: Dict = np.random.default_rng(seed=snake_case_ )
# Roughly 25% of the qubits will contr... | 355 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> list[list[float]]:
A: list[list[float]] = []
for data in source_data:
for i, el in enumerate(__lowercase ):
if len(__lowercase ) < i + 1:
da... | 334 | 0 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class lowerCAmelCase_ ( __UpperCamelCase , __UpperCamelC... | 356 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_... | 334 | 0 |
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