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 requests
from bsa import BeautifulSoup
def SCREAMING_SNAKE_CASE( __lowercase = "AAPL" ) -> str:
A: Any = F"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
A: int = BeautifulSoup(requests.get(__lowe... | 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'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispe... | 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'''
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
... | 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'''
import itertools
import string
from collections.abc import Generator, Iterable
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> Generator[tuple[str, ...], None, None]:
A: List[str] = iter(__lowercase )
while True:... | 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 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 |
'''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 re
def SCREAMING_SNAKE_CASE( __lowercase ) -> str:
if len(re.findall('''[ATCG]''' , __lowercase ) ) != len(__lowercase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' ... | 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'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> Any:
A: Dict = {
'''en''': '''Machine learning is great, isn\... | 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 argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcesso... | 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'''
# 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/... | 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 itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCamelCase = '''\
@misc{chen2021evaluating,... | 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 copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( 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'''
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,
resca... | 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 ) -> str:
A: Optional[int] = 0
# if input_string is "aba" than new_input_string become "a|b|a"
A: int = ''''''
A: Tuple = ''''''
# append... | 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 os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase=7 ) -> List[Any]:
A: List[Any] = None
if token is not ... | 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 torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCase = logg... | 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 collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
UpperCamelCase = TypeVar('''KEY''')
UpperCamelCase = TypeVar('''VAL''')
@dataclass(frozen=UpperCAmelCase_ , slots=UpperC... | 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 TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 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 unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
... | 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'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> int:
if len(__lowercase ) != len(__lowercase ):
raise ValueError('''String lengths must match!''' )
A: str = 0
for chara, chara in zip(__l... | 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'''
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''vocab_file''': ''... | 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 tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
UpperCamelCase_ : int = (PNDMSche... | 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'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {'''configuration_plbart''': ['''PLBART_PRETRAI... | 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'''
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 |
'''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 json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
UpperCamelCase = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE( __lowercas... | 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'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import loggin... | 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 typing import Dict, Optional
import numpy as np
import datasets
UpperCamelCase = '''
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For ... | 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 glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check... | 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 random
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
A: List[str] = num - 1
A: Any = 0
while s % 2 == 0:
A: str = s // 2
t += 1
for _ in range(5 ... | 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'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
'''configuration_clipseg''': [
'''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''CLIPSegConfig''',
... | 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'''
from __future__ import annotations
from math import pow, sqrt
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> dict[str, float]:
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueError('''... | 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 json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
UpperCamelCase = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerr... | 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 warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
... | 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'''
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[Any] , SCREAMING_SNAKE_CASE_ : int ) -> Optional[Any]:
'''simple docstring'''
A: List[Any] ... | 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'''
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 |
'''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 logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
UpperCamelCase = logging.getLogger(__name__)
@dataclass
class lowerCAmelC... | 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
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class ... | 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'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> str:
return " ".join(
''''''.join(word[::-1] ) if len(__lowercase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
pri... | 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 doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
... | 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 TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_text_dual_encoder''': ['''VisionT... | 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 re
import string
import numpy as np
import datasets
UpperCamelCase = '''
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
'''
UpperCamelCase = ... | 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
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFM... | 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'''
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_com... | 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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_roformer''... | 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 typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {'''v... | 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 __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 TFModelTesterMixin,... | 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 absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import s... | 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'''
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
... | 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 typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...s... | 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'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class lowerCAmelCase_ :
'''s... | 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 copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TO... | 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 io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
... | 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'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 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 inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
f... | 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 typing import TYPE_CHECKING
from ..utils import _LazyModule
UpperCamelCase = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
... | 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 warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
... | 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 math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> float:
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensity
... | 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 unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_co... | 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 logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
UpperCamelCase = logging.getLogger(__name__)
class lowerCAmelCase_ ( UpperCAmelCa... | 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'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=False ) -> Optional[int]:
if isinstance(__lowercase , __lowercase ) and isinstance(__lowercase , __lowercase ):
A: Union[str, Any]... | 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
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 |
'''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 TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_speec... | 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 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 = {
'''face... | 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 copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase = logging... | 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 maths.prime_factors import prime_factors
def SCREAMING_SNAKE_CASE( __lowercase ) -> int:
if not isinstance(__lowercase , __lowercase ):
A: Any = F"""Input value of [number={number}] must be an integer"""
... | 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 __future__ import annotations
from typing import Any
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : int = 6 ) -> None:
... | 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 copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, ... | 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 collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
UpperCamelCase = collections.na... | 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'''
from manim import *
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
def _snake_case ( self : int ) -> int:
'''simple docstring'''
A: List[str] ... | 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'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
UpperCamelCase ... | 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'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_log... | 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 unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
def _snake_case ( self : Dict ) -> List[Any]:
... | 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 math
import flax.linen as nn
import jax.numpy as jnp
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase = 1 , __lowercase = 1 , __lowercase = 1.0E4 , __lowercase = False , __lowercase = ... | 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 baseaa
def SCREAMING_SNAKE_CASE( __lowercase ) -> bytes:
return baseaa.aaaencode(string.encode('''utf-8''' ) )
def SCREAMING_SNAKE_CASE( __lowercase ) -> str:
return baseaa.aaadecode(__lowercase ).decode('''utf-8''' )
if... | 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'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase = {
'''facebook/... | 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'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> float:
def get_matched_characters(__lowercase , __lowercase ) -> str:
A: Union[str, Any] = []
A: Optional[int] = min(... | 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'''
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def SCREAMING_SNAKE_CASE( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) =... | 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 List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
UpperCamelCase = logging.get_logger(__name... | 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 __future__ import annotations
UpperCamelCase = list[list[int]]
# assigning initial values to the grid
UpperCamelCase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0... | 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 ) -> bool:
if p < 2:
raise ValueError('''p should not be less than 2!''' )
elif p == 2:
return True
A: List[Any] = 4
A: int = (1 << p) - 1... | 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 collections import deque
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNA... | 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 pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCAmelCase_ ( unittest.TestCase ):
'''... | 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 json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common im... | 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 inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision... | 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 faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
imp... | 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 TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
... | 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 __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> float:
if days_between_payments <= 0:
raise ValueError('''days_between_payments must be > 0''' )
if daily_interest_r... | 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'''
def SCREAMING_SNAKE_CASE( __lowercase ) -> list:
A: List[Any] = False
while is_sorted is False: # Until all the indices are traversed keep looping
A: Optional[Any] = True
for i in range(0 , ... | 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 tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, requi... | 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'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCamelCase = {'''processing_wav2vec2_with_lm''': ['''Wav2Vec2ProcessorWithLM''']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import ... | 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'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
UpperCamelCase_ : Tuple = ["""image_... | 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 = 1_0 ) -> str:
if not isinstance(__lowercase , __lowercase ) or n < 0:
raise ValueError('''Invalid input''' )
A: List[str] = 1_0**n
A: Tuple = ... | 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 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'''],
... | 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'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 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 json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor... | 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'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
UpperCamelCase = {'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
raise Option... | 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
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasonin... | 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 logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Co... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
... | 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 argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 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 |
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