code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musicgen... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : int = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", "... | 102 | 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,
AdamW,
... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__magic_name__ : Any = logging.get_logger(__name__)
__magic_name__ ... | 102 | 1 |
"""simple docstring"""
from __future__ import annotations
__magic_name__ : List[Any] = list[list[int]]
# assigning initial values to the grid
__magic_name__ : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, ... | 102 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, ... | 102 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Union[str, Any] = logging.get_logger(__name__)
__magic_name__ : List[Any] = {
# See all MEGATRON_BERT models at https://huggingface.co... | 102 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return math.pow(SCREAMING_SNAKE_CASE , 2 ) - a
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return 2 * x
def UpperCamelC... | 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Any = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_t... | 102 |
"""simple docstring"""
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase__ ( __SCREAMING_SNAKE_CASE )... | 102 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Optional[Any] = logging.get_logger(__name__)
__magic_name__ : Tuple = {
"""google/realm-cc-news-pretrained-embedder""": (
"""... | 102 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoenco... | 102 | 1 |
"""simple docstring"""
import qiskit
def UpperCamelCase (SCREAMING_SNAKE_CASE = 2 ):
UpperCamelCase : List[Any] = qubits
# Using Aer's simulator
UpperCamelCase : int = qiskit.Aer.get_backend("""aer_simulator""" )
# Creating a... | 102 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Optional[int] = x
UpperCamelCase : str = ... | 102 | 1 |
"""simple docstring"""
import functools
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
# Validation
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or not all(isinstance(SCREAMING_SNAKE_CASE , SCREAM... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : List[str] = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https... | 102 | 1 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, ... | 102 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Dict = sorted(zip(SCREA... | 102 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import ... | 102 |
"""simple docstring"""
import os
def UpperCamelCase ():
UpperCamelCase : Union[str, Any] = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , """num.txt""" )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(S... | 102 | 1 |
"""simple docstring"""
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.trans... | 102 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
__magic_name__ : Dict = logging.getLogger(__name__)
@dataclass
c... | 102 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase : str = """"""
UpperCamelCase : Dict = """"""
... | 102 | 1 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
# Checks if the entire collection has been sorted
if len(SCREAMING_SNAKE_CASE ) <= 1 or n <= 1:
return
insert_... | 102 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musicgen... | 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : int = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", "... | 102 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
def count_of_possible_combinations(SCREAMING_SNAKE_CASE ) -> int:
if target < 0:
return 0
if targ... | 102 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_incr... | 102 | 1 |
"""simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_... | 102 |
"""simple docstring"""
from math import ceil, sqrt
def UpperCamelCase (SCREAMING_SNAKE_CASE = 100_0000 ):
UpperCamelCase : int = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
Uppe... | 102 | 1 |
"""simple docstring"""
import numpy
class lowercase__ :
"""simple docstring"""
def __init__( self , _A , _A ):
'''simple docstring'''
UpperCamelCase : Dict = input_array
... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : List[Any] = """"""
for i in table:
res += inp[i - 1]
return res
def UpperCamelCase (SCREAMING_SNAKE_CASE ):... | 102 | 1 |
"""simple docstring"""
__magic_name__ : dict[tuple[int, int, int], int] = {}
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
# if we are absent twice, or late 3 consecutive days,
# no furthe... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Dict = {
"""conf... | 102 | 1 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 102 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 102 | 1 |
"""simple docstring"""
from math import factorial
def UpperCamelCase (SCREAMING_SNAKE_CASE = 100 ):
return sum(map(SCREAMING_SNAKE_CASE , str(factorial(SCREAMING_SNAKE_CASE ) ) ) )
if __name__ == "__main__":
print(solution(int(input("""Enter th... | 102 |
"""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 im... | 102 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_alig... | 102 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : List[Any] = {
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
... | 102 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...t... | 102 | 1 |
"""simple docstring"""
from math import sqrt
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) and (
number >= 0
), "'number' must been an int and positive"
UpperCamelCase : D... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : int = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", "... | 102 | 1 |
"""simple docstring"""
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__mag... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__magic_name__ : Any = logging.get_logger(__name__)
__magic_name__ ... | 102 | 1 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDoc... | 102 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, ... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase : str = """"""
UpperCamelCase : Dict = """"""
... | 102 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return math.pow(SCREAMING_SNAKE_CASE , 2 ) - a
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return 2 * x
def UpperCamelC... | 102 | 1 |
"""simple docstring"""
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ... | 102 |
"""simple docstring"""
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase__ ( __SCREAMING_SNAKE_CASE )... | 102 | 1 |
"""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/li... | 102 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoenco... | 102 | 1 |
"""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,
PNDMSched... | 102 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Optional[int] = x
UpperCamelCase : str = ... | 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Dict = {
"""conf... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : List[str] = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https... | 102 | 1 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with t... | 102 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Dict = sorted(zip(SCREA... | 102 | 1 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
__lowerCAmelCase : List[Any] = (CMStoch... | 102 |
"""simple docstring"""
import os
def UpperCamelCase ():
UpperCamelCase : Union[str, Any] = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , """num.txt""" )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(S... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE = 6008_5147_5143 ):
try:
UpperCamelCase : Optional[Any] = int(SCREAMING_SNAKE_CASE )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or cas... | 102 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
__magic_name__ : Dict = logging.getLogger(__name__)
@dataclass
c... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
assert x is not None
assert y is not None
UpperCamelCase : str = len(SCREAMING_SNAKE_CASE )
UpperCamelCase : List[str] = len(SCREA... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase : str = """"""
UpperCamelCase : Dict = """"""
... | 102 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
__magic_name__ : List[Any] = ["""small""", """medium""", """large"""]
__magic_name__ : int = """lm_head.decoder.weight"""
__magic_name__ : ... | 102 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musicgen... | 102 | 1 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 102 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 102 | 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
__magic_name__ : Dict = logging.getLogger(__name__)
class lowercase__ ... | 102 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_incr... | 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : List[Any] = {
"""configuration_autoformer""": [
"""AUTOFORMER_PRETRA... | 102 |
"""simple docstring"""
from math import ceil, sqrt
def UpperCamelCase (SCREAMING_SNAKE_CASE = 100_0000 ):
UpperCamelCase : int = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
Uppe... | 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : List[str] = {
"""configuration_convnext""": ["... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : List[Any] = """"""
for i in table:
res += inp[i - 1]
return res
def UpperCamelCase (SCREAMING_SNAKE_CASE ):... | 102 | 1 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBa... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Dict = {
"""conf... | 102 | 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()
clas... | 102 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 102 | 1 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE = 100 ):
UpperCamelCase : Union[str, Any] = sum(i * i for i in range(1 , n + 1 ) )
UpperCamelCase : int = int(math.pow(sum(range(1 , n + 1 ... | 102 |
"""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 im... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
if index == number_of_items:
return 0
UpperCamelCase : Opt... | 102 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return " ".join(
"""""".join(word[::-1] ) if len(SCREAMING_SNAKE_CASE ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
... | 102 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...t... | 102 | 1 |
"""simple docstring"""
from math import sqrt
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even number... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : int = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", "... | 102 | 1 |
"""simple docstring"""
import re
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = re.compile(
r"""^(?:0|94|\+94|0{2}94)""" r"""7(0|1|2|4|5|6|7|8)""" r"""(-| |)""" r"""\d{7}$""" )
return bool(re.search(SCREAMING_SNAKE_CASE ... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__magic_name__ : Any = logging.get_logger(__name__)
__magic_name__ ... | 102 | 1 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
i... | 102 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, ... | 102 | 1 |
"""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 UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING... | 102 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return math.pow(SCREAMING_SNAKE_CASE , 2 ) - a
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return 2 * x
def UpperCamelC... | 102 | 1 |
"""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,
get_resize_output_image_size,
normalize,
rescale,
... | 102 |
"""simple docstring"""
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase__ ( __SCREAMING_SNAKE_CASE )... | 102 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : str = logging.get_logger(__name__)
__magic_name__ : Union[str, Any] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rw... | 102 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoenco... | 102 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ : Any = logging.get_logger(__name__)
__ma... | 102 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Optional[int] = x
UpperCamelCase : str = ... | 102 | 1 |
"""simple docstring"""
import qiskit
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Union[str, Any] = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : List[str] = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https... | 102 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available... | 102 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Dict = sorted(zip(SCREA... | 102 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 102 |
"""simple docstring"""
import os
def UpperCamelCase ():
UpperCamelCase : Union[str, Any] = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , """num.txt""" )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(S... | 102 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
# vision encoder
if "img_encoder.pos_embed" in name:
... | 102 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
__magic_name__ : Dict = logging.getLogger(__name__)
@dataclass
c... | 102 | 1 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase : str = """"""
UpperCamelCase : Dict = """"""
... | 102 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class lowercase__ ... | 102 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musicgen... | 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : Any = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
... | 102 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 102 | 1 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not... | 102 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_incr... | 102 | 1 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class lowercase__ :
"""simple docstring"""
def __init__( self , _A ):
'''simple docstring'''
... | 102 |
"""simple docstring"""
from math import ceil, sqrt
def UpperCamelCase (SCREAMING_SNAKE_CASE = 100_0000 ):
UpperCamelCase : int = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
Uppe... | 102 | 1 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipe... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : List[Any] = """"""
for i in table:
res += inp[i - 1]
return res
def UpperCamelCase (SCREAMING_SNAKE_CASE ):... | 102 | 1 |
"""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... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Dict = {
"""conf... | 102 | 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,
)
__magic_name__ : Any = {
"""configu... | 102 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 102 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ : int = logging.get_logger(__name__)
__magic_name__ :... | 102 |
"""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 im... | 102 | 1 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
__magic_name__ : Any = TypeVar("""T""")
__magic_name__ : Optional[Any] = Union[List[T], Tuple[T, ...]]
__magic_name__ : Optional[Any] = Union[T, List[T], Di... | 102 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 102 | 1 |
"""simple docstring"""
from collections.abc import Sequence
from queue import Queue
class lowercase__ :
"""simple docstring"""
def __init__( self , _A , _A , _A , _A=None , _A=None ):
'''simp... | 102 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...t... | 102 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREA... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : int = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", "... | 102 | 1 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class lowercase__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
d... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__magic_name__ : Any = logging.get_logger(__name__)
__magic_name__ ... | 102 | 1 |
"""simple docstring"""
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
__magic_name__ : Union[str, Any] = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
__magic_name__ : Optional[int]... | 102 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, ... | 102 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
__magic_name__ : Dict = False
__magic_name__ : str = True
__magic_name__ ... | 102 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return math.pow(SCREAMING_SNAKE_CASE , 2 ) - a
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return 2 * x
def UpperCamelC... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
while a != 0:
UpperCamelCase , UpperCamelCase : Any = b % a, a
return b
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCR... | 102 |
"""simple docstring"""
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase__ ( __SCREAMING_SNAKE_CASE )... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
_enforce_args(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
if n == 0:
return 0
UpperCamelCase : List[str] = float("""-inf""" ... | 102 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoenco... | 102 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 102 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Optional[int] = x
UpperCamelCase : str = ... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : str = len(SCREAMING_SNAKE_CASE )
for _ in range(SCREAMING_SNAKE_CASE ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : List[str] = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https... | 102 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_t... | 102 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Dict = sorted(zip(SCREA... | 102 | 1 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return math.pow(SCREAMING_SNAKE_CASE , 2 ) - a
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return 2 * x
def UpperCamelC... | 102 |
"""simple docstring"""
import os
def UpperCamelCase ():
UpperCamelCase : Union[str, Any] = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , """num.txt""" )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(S... | 102 | 1 |
"""simple docstring"""
__magic_name__ : str = {
"""A""": """.-""", """B""": """-...""", """C""": """-.-.""", """D""": """-..""", """E""": """.""", """F""": """..-.""", """G""": """--.""",
"""H""": """....""", """I""": """..""", """J""": """.---""", """K""": """-.-""", """L"""... | 102 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
__magic_name__ : Dict = logging.getLogger(__name__)
@dataclass
c... | 102 | 1 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import to... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase : str = """"""
UpperCamelCase : Dict = """"""
... | 102 | 1 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 102 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musicgen... | 102 | 1 |
"""simple docstring"""
import random
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : Tuple = num - 1
UpperCamelCase : Tuple = 0
while s % 2 == 0:
UpperCamelCase : Any = s // 2
t += 1
... | 102 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 102 | 1 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
__magic_name__ : Tuple = [int(0.5 * n * (n + 1)) for n in range(1, 1_0_1)]
def UpperCamelCase ():
UpperCamelCase : List[Any] = os.path.dirname(os.path.realpath... | 102 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_incr... | 102 | 1 |
"""simple docstring"""
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
__lowerCAmelCase : List[Any] = (DDIMParallelSche... | 102 |
"""simple docstring"""
from math import ceil, sqrt
def UpperCamelCase (SCREAMING_SNAKE_CASE = 100_0000 ):
UpperCamelCase : int = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
Uppe... | 102 | 1 |
"""simple docstring"""
from ... import PretrainedConfig
__magic_name__ : Optional[Any] = {
"""sijunhe/nezha-cn-base""": """https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json""",
}
class lowercase__ ( __SCREAMING_SNAKE_CASE ):
... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : List[Any] = """"""
for i in table:
res += inp[i - 1]
return res
def UpperCamelCase (SCREAMING_SNAKE_CASE ):... | 102 | 1 |
"""simple docstring"""
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def ... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Dict = {
"""conf... | 102 | 1 |
"""simple docstring"""
import os
def UpperCamelCase ():
UpperCamelCase : Union[str, Any] = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , """num.txt""" )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(S... | 102 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 102 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ : ... | 102 |
"""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 im... | 102 | 1 |
"""simple docstring"""
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
__magic_name__ : List[Any] = {
# ... | 102 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 102 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class ... | 102 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...t... | 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
__magic_name__ : Optional[int] = {
"""configuration_speecht5""": [
""... | 102 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : int = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", "... | 102 | 1 |
"""simple docstring"""
from collections import deque
class lowercase__ :
"""simple docstring"""
def __init__( self , _A , _A , _A ):
'''simple docstring'''
UpperCamelCase : int ... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__magic_name__ : Any = logging.get_logger(__name__)
__magic_name__ ... | 102 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_input... | 102 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, ... | 102 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__magic_name__ : Union[str, Any] = {"""configuration_vit_mae""": ["""V... | 102 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return math.pow(SCREAMING_SNAKE_CASE , 2 ) - a
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return 2 * x
def UpperCamelC... | 102 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
f... | 102 |
"""simple docstring"""
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase__ ( __SCREAMING_SNAKE_CASE )... | 102 | 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_... | 102 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoenco... | 102 | 1 |
"""simple docstring"""
import math
import os
import sys
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : Optional[Any] = """"""
try:
with open(SCREAMING_SNAKE_CASE , """rb""" ) as binary_file:
UpperC... | 102 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Optional[int] = x
UpperCamelCase : str = ... | 102 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_avai... | 102 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : List[str] = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https... | 102 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import Att... | 102 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Dict = sorted(zip(SCREA... | 102 | 1 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
if principal <= 0:
raise Exception("""Principal borrowed must be > 0""" )
if rate_per_annum < 0:
raise Exceptio... | 102 |
"""simple docstring"""
import os
def UpperCamelCase ():
UpperCamelCase : Union[str, Any] = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , """num.txt""" )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(S... | 102 | 1 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class lowercase__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
__lowerCAmelCase : Optional[Any] = """Speech2TextFeatur... | 102 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
__magic_name__ : Dict = logging.getLogger(__name__)
@dataclass
c... | 102 | 1 |
"""simple docstring"""
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nest... | 102 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase : str = """"""
UpperCamelCase : Dict = """"""
... | 102 | 1 |
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