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"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> str:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 350 | """simple docstring"""
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 2 | 0 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase (A_... | 351 | """simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__... | 2 | 0 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_ava... | 352 | """simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class UpperCAmelCase :
"""simple docstring"""
_UpperCAmelCase :s... | 2 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_availabl... | 353 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docs... | 2 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"
)... | 354 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = 5_0 ) -> int:
lowercase__: str = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_leng... | 2 | 0 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__A = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
autho... | 355 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 2 | 0 |
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase = 0 ) -> list:
lowercase__: int = length or len(__A )
lowercase__: List[str] = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
lowercase__, lowercase__: int = ... | 356 | """simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase (_UpperCAmelCase ,unittest.TestCase ):
"""simple docstring"""... | 2 | 0 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> List[str]:
lowercase__: List[str] = np.max(lowerCamelCase_ , axis=-1 , keepdims=lowerCamelCase_ )
lowercase__: List[Any] = np.exp(outputs ... | 357 | """simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__A = "<<<<<<< This should probably be modified because it mentions: "
__A = "=... | 2 | 0 |
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_xl.tokenization_transfo_xl import CORPUS_NAME,... | 358 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at https://huggingf... | 2 | 0 |
"""simple docstring"""
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> Dict:
return 1 / (1 + np.exp(-z ... | 359 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__A = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the model ... | 2 | 0 |
"""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 TOKEN, USER, is_stag... | 360 | """simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 2 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_m... | 361 | """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
__A = logging.get_logger(__name__)
__A = {
"micro... | 2 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 362 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
lowercase__: int = ''''''
for word_or_phrase in separated:
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise Exception('''join() accepts only strings to... | 2 | 0 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> List[str]:
lowercase__: Dict = args.pruning_method
lowercase__: ... | 363 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 2 | 0 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import ... | 364 | """simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__A = get_tests_dir("fixtu... | 2 | 0 |
"""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
__A = logging.get_logger(__name__)
_... | 365 | """simple docstring"""
import unittest
from transformers import DonutProcessor
__A = "naver-clova-ix/donut-base"
class UpperCAmelCase (unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ):
lowercase__: int = DonutProcessor.fr... | 2 | 0 |
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> str:
return " ".join(
''''''.join(word[::-1] ) if len(a_ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words("Hey wollef sroirraw"))
| 366 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
__A = logging.get_logger(__name__)
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docstring"""
def __init__( self , *_UpperCAme... | 2 | 0 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMaskedLM,
DistilBert... | 367 | """simple docstring"""
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx... | 2 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.... | 368 | """simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWit... | 2 | 0 |
"""simple docstring"""
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils i... | 369 | """simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Config... | 2 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__A = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> List[int]:
if isinstance(UpperCAmelCase__ , np.ndarra... | 370 | """simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/unispeech-sat-base-100h-libri-ft": (
"https://huggingface.co/microsoft/unispeec... | 2 | 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,
)
__A = {
"configuration_blenderbot": [
"BLENDERBOT_PRET... | 371 | """simple docstring"""
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
__A = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", defau... | 2 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json",
}
class U... | 350 | """simple docstring"""
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 2 | 0 |
"""simple docstring"""
import unittest
from transformers import DebertaConfig, 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_common import ModelTes... | 351 | """simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__... | 2 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fro... | 352 | """simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class UpperCAmelCase :
"""simple docstring"""
_UpperCAmelCase :s... | 2 | 0 |
"""simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, loggin... | 353 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docs... | 2 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class UpperCAmelCase (_UpperCAmelCase ):
"... | 354 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = 5_0 ) -> int:
lowercase__: str = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_leng... | 2 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 355 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 2 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
__A = logging.... | 356 | """simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase (_UpperCAmelCase ,unittest.TestCase ):
"""simple docstring"""... | 2 | 0 |
"""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 (
HPSearchBackend,
default_hp_... | 357 | """simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__A = "<<<<<<< This should probably be modified because it mentions: "
__A = "=... | 2 | 0 |
import math
import os
import sys
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> str:
lowercase__: Any = ''''''
try:
with open(_UpperCamelCase , '''rb''' ) as binary_file:
lowercase__: List[Any] = binary_file.read()
for dat in data:
lowercas... | 358 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at https://huggingf... | 2 | 0 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggi... | 359 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__A = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the model ... | 2 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
__A = {
'configuration_speech_to_text': ['SPEECH_TO_TEXT_... | 360 | """simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> str:
if isinstance(lowercase_ , lowercase_ ):
raise TypeError('''\'float\' object cannot be interpreted as an integer''' )
if isinstance(lowercase_ , lowercase_ ):
raise TypeError('''\'... | 361 | """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
__A = logging.get_logger(__name__)
__A = {
"micro... | 2 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_configuration_common import ... | 362 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
lowercase__: int = ''''''
for word_or_phrase in separated:
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise Exception('''join() accepts only strings to... | 2 | 0 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import requi... | 363 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 2 | 0 |
"""simple docstring"""
import torch
from transformers import AutoModel
class UpperCAmelCase (torch.nn.Module ):
"""simple docstring"""
def __init__( self , _UpperCAmelCase="sayef/fsner-bert-base-uncased" ):
super(UpperCAmelCase_ , self ).__init__()
... | 364 | """simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__A = get_tests_dir("fixtu... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> int:
if n == 1 or not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
return 0
elif n == 2:
return 1
else:
lowercase__: List[str] = [0, 1]
for i in range(2 , n + 1 ... | 365 | """simple docstring"""
import unittest
from transformers import DonutProcessor
__A = "naver-clova-ix/donut-base"
class UpperCAmelCase (unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ):
lowercase__: int = DonutProcessor.fr... | 2 | 0 |
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
if is_torch_available():
import torc... | 366 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
__A = logging.get_logger(__name__)
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docstring"""
def __init__( self , *_UpperCAme... | 2 | 0 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase (metaclass=A_ ):
"""simple docstring"""
_UpperCAmelCase :Optional[Any] = ["torch", "torchsde"]
def __init__( self , *_UpperCAmelCase , **_UpperCAmelCase ):
requires_bac... | 367 | """simple docstring"""
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx... | 2 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...feature... | 368 | """simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWit... | 2 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
__A = logging.get_logger(__name__)
... | 369 | """simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Config... | 2 | 0 |
"""simple docstring"""
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> list[int]:
return [ord(_lowerCAmelCase ) - 9_6 for elem in plain]
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> str:
return "".join(chr(elem + 9_6 ) for e... | 370 | """simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/unispeech-sat-base-100h-libri-ft": (
"https://huggingface.co/microsoft/unispeec... | 2 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization... | 371 | """simple docstring"""
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
__A = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", defau... | 2 | 0 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...m... | 350 | """simple docstring"""
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 2 | 0 |
"""simple docstring"""
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> Optional[Any]:
return x + 2
class UpperCAmelCase (unittest.TestCase ):
... | 351 | """simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__... | 2 | 0 |
"""simple docstring"""
import math
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> Tuple:
return math.pow(lowerCamelCase__ , 2 ) - a
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> List[str]:
return 2 * x
def SCREAMING_SNAKE_CASE__ (... | 352 | """simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class UpperCAmelCase :
"""simple docstring"""
_UpperCAmelCase :s... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> int:
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
lowercase__: Tuple = 0
while number:
# Thi... | 353 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docs... | 2 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowerCAmelCase_... | 354 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = 5_0 ) -> int:
lowercase__: str = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_leng... | 2 | 0 |
"""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_video_inputs
if is_torch_av... | 355 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 2 | 0 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> List[str]:
lowercase__: Optional[int] = {}
lowercase__: List[str] = job['''started_at''']
lowercase__: Optional[int] ... | 356 | """simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase (_UpperCAmelCase ,unittest.TestCase ):
"""simple docstring"""... | 2 | 0 |
"""simple docstring"""
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_... | 357 | """simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__A = "<<<<<<< This should probably be modified because it mentions: "
__A = "=... | 2 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_commo... | 358 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at https://huggingf... | 2 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}
class Upp... | 359 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__A = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the model ... | 2 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, i... | 360 | """simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 2 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, ... | 361 | """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
__A = logging.get_logger(__name__)
__A = {
"micro... | 2 | 0 |
"""simple docstring"""
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class UpperCAmelCase (pl.LightningModule ):
"""simple docstring"""
def __init__( self , _UpperCAmel... | 362 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
lowercase__: int = ''''''
for word_or_phrase in separated:
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise Exception('''join() accepts only strings to... | 2 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 363 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 2 | 0 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
fro... | 364 | """simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__A = get_tests_dir("fixtu... | 2 | 0 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class UpperCAmelCase (_UpperCAmelCase ):
"""simpl... | 365 | """simple docstring"""
import unittest
from transformers import DonutProcessor
__A = "naver-clova-ix/donut-base"
class UpperCAmelCase (unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ):
lowercase__: int = DonutProcessor.fr... | 2 | 0 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoConfig,
AutoF... | 366 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
__A = logging.get_logger(__name__)
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docstring"""
def __init__( self , *_UpperCAme... | 2 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> list[list[int]]:
lowercase__: list[list[int]] = []
lowercase__: list[int] = []
lowercase__: str = 0
lowercase__: Dict = sum(__UpperCAmelCase )
... | 367 | """simple docstring"""
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx... | 2 | 0 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> list[list[float]]:
lowercase__: Tuple = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works ... | 368 | """simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWit... | 2 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_gra... | 369 | """simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Config... | 2 | 0 |
"""simple docstring"""
from __future__ import annotations
class UpperCAmelCase :
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
lowercase__: List[str] = TypeError(
'''Matrices must be formed from a list of zero or more lists conta... | 370 | """simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/unispeech-sat-base-100h-libri-ft": (
"https://huggingface.co/microsoft/unispeec... | 2 | 0 |
"""simple docstring"""
__A = [
[0, 1_6, 1_3, 0, 0, 0],
[0, 0, 1_0, 1_2, 0, 0],
[0, 4, 0, 0, 1_4, 0],
[0, 0, 9, 0, 0, 2_0],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __Upp... | 371 | """simple docstring"""
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
__A = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", defau... | 2 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> float:
return sum(c * (x**i) for i, c in enumerate(_SCREAMING_SNAKE_CASE ) )
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase... | 350 | """simple docstring"""
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = 1_0_0_0 ) -> Tuple:
lowercase__: Any = 2**power
lowercase__: Optional[Any] = str(UpperCamelCase__ )
lowercase__: Union[str, Any] = list(UpperCamelCase__ )
lowercase__: Optional[in... | 351 | """simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__... | 2 | 0 |
"""simple docstring"""
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMix... | 352 | """simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class UpperCAmelCase :
"""simple docstring"""
_UpperCAmelCase :s... | 2 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms imp... | 353 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docs... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
return number | (1 << position)
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
return number & ~(1 << position)
def SCREAMING_SNAKE_CASE__ ... | 354 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = 5_0 ) -> int:
lowercase__: str = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_leng... | 2 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fro... | 355 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 2 | 0 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase=5 ) -> Optional[Any]:
# Adapted from https://github.com/pytorch/fairseq/blob/master/fairseq/models/roberta/hub... | 356 | """simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase (_UpperCAmelCase ,unittest.TestCase ):
"""simple docstring"""... | 2 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_te... | 357 | """simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__A = "<<<<<<< This should probably be modified because it mentions: "
__A = "=... | 2 | 0 |
# flake8: noqa
# Lint as: python3
__A = [
"VerificationMode",
"Version",
"disable_progress_bar",
"enable_progress_bar",
"is_progress_bar_enabled",
"experimental",
]
from .info_utils import VerificationMode
from .logging import disable_progress_bar, enable_progress_bar, is_progress... | 358 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at https://huggingf... | 2 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tenso... | 359 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__A = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the model ... | 2 | 0 |
"""simple docstring"""
from random import randint, random
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = False , __UpperCAmelCase = False , __UpperCAmelCase = 5 , ) -> Union[str, Any]:
lowercase__ = [[-1] * number_of_cells... | 360 | """simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 2 | 0 |
"""simple docstring"""
import sys
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> Any:
lowercase__: Optional[Any] = len(__lowerCAmelCase )
lowercase__: List[str] = [[0 for x in range(__lowerCAmelCase )] for x in range(__lowerCAmelCase )]
lowercase__: ... | 361 | """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
__A = logging.get_logger(__name__)
__A = {
"micro... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> float:
if edge <= 0 or not isinstance(_lowercase , _lowercase ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((2_5 + 1_0 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def SCREAMING_SN... | 362 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
lowercase__: int = ''''''
for word_or_phrase in separated:
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise Exception('''join() accepts only strings to... | 2 | 0 |
"""simple docstring"""
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__A = """src/transformers"""
# This is to... | 363 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 2 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at https://huggingf... | 364 | """simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__A = get_tests_dir("fixtu... | 2 | 0 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def SCREAMING_SNAKE_CASE__ ( ) -> str:
lowercase__: Any = ArgumentParser(
description=(
... | 365 | """simple docstring"""
import unittest
from transformers import DonutProcessor
__A = "naver-clova-ix/donut-base"
class UpperCAmelCase (unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ):
lowercase__: int = DonutProcessor.fr... | 2 | 0 |
import os
from datetime import datetime as dt
from github import Github
__A = [
"good first issue",
"good second issue",
"good difficult issue",
"enhancement",
"new pipeline/model",
"new scheduler",
"wip",
]
def SCREAMING_SNAKE_CASE__ ( ) -> int:
lowercase... | 366 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
__A = logging.get_logger(__name__)
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docstring"""
def __init__( self , *_UpperCAme... | 2 | 0 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {"vocab_file": "vocab.json", "merges... | 367 | """simple docstring"""
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx... | 2 | 0 |
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> Any:
if num <= 0:
lowercase__: int = F"""{num}: Invalid input, please enter a positive integer."""
raise ValueError(__UpperCamelCase )
lowercase__: Any = [True] *... | 368 | """simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWit... | 2 | 0 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
__A = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a M... | 369 | """simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Config... | 2 | 0 |
"""simple docstring"""
__A = [0, 2, 4, 6, 8]
__A = [1, 3, 5, 7, 9]
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> Optional[int]:
if remaining_length == 0:
if digits[0] == 0 or digits[-1] ... | 370 | """simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/unispeech-sat-base-100h-libri-ft": (
"https://huggingface.co/microsoft/unispeec... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = 1_0_0_0 ) -> Tuple:
return sum(e for e in range(3 , __a ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f'''{solution() = }''')
| 371 | """simple docstring"""
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
__A = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", defau... | 2 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAm... | 350 | """simple docstring"""
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 2 | 0 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__A : List[str] = False
class UpperCAmelCase ... | 351 | """simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__... | 2 | 0 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = "isbn/0140328726" ) -> str:
lowercase__: Dict = olid.strip().strip('''/''' ) # Remove leading/trailing whi... | 352 | """simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class UpperCAmelCase :
"""simple docstring"""
_UpperCAmelCase :s... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> List[Any]:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase=0 ) -> Optional[int]:
return... | 353 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docs... | 2 | 0 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__A = 3
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> Optional[int]:
print('''Generating primitive root of p''' )
while True:
lowe... | 354 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = 5_0 ) -> int:
lowercase__: str = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_leng... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
lowercase__: Optional[Any] = [1]
for i in range(2 , lowerCamelCase_ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k out of bounds"
l... | 355 | """simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 2 | 0 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase = "laptop" ) -> DataFrame:
lowercase__: Tuple = F"""https://www.amazon.in/laptop/s?k={product}"""
lowercase__: Any = {
... | 356 | """simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase (_UpperCAmelCase ,unittest.TestCase ):
"""simple docstring"""... | 2 | 0 |
"""simple docstring"""
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTok... | 357 | """simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__A = "<<<<<<< This should probably be modified because it mentions: "
__A = "=... | 2 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
AutoTokenizer,
... | 358 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at https://huggingf... | 2 | 0 |
"""simple docstring"""
from statistics import mean
import numpy as np
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> list:
lowercase__: Optional[Any] = 0
# Number of processes finished
lowercase__: ... | 359 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__A = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the model ... | 2 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
return "\n".join(
F"""{number} * {i} = {number * i}""" for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_table(number=5, number_of_te... | 360 | """simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 2 | 0 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> bool:
return (
num != den and num % 1_0 == den // 1_0 and (num // 1_0) / (den % 1_0) == num / den
)
def SCREAMI... | 361 | """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
__A = logging.get_logger(__name__)
__A = {
"micro... | 2 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.