code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipeline... | 35 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> tuple[float, list[float]]:
UpperCamelCase = list(range(len(__UpperCamelCase ) ) )
UpperCame... | 35 | 1 |
'''simple docstring'''
from math import sqrt
def lowercase__ ( __UpperCamelCase )-> bool:
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, ... | 35 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'SenseTime/deformable-detr... | 35 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffu... | 35 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowercase__ ( __UpperCamelCase )-> Any:
UpperCamelCase = [
"""encoder.version""",
... | 35 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase )-> None:
create_state_space_tree(__UpperCamelCase , [] , 0 , [0 for i in range(len(__UpperCamelCase ) )] )
def lowercase__ ( __Upp... | 35 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 35 | 1 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
SCREAMING_SNAKE_CASE__ = 'examples/'
SCREAMING_SNAKE_CASE__ = {
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),... | 35 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDM... | 35 | 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... | 35 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
... | 35 | 1 |
'''simple docstring'''
import random
def lowercase__ ( __UpperCamelCase )-> bool:
UpperCamelCase = num - 1
UpperCamelCase = 0
while s % 2 == 0:
UpperCamelCase = s // 2
t +... | 35 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 8.31_44_62 # Unit - J mol-1 K-1
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError("""Invalid ... | 35 | 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... | 35 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set... | 35 | 1 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE__ = {'UserAgent': UserAgent().random}
def lowercase__ ( __UpperCamelCase )-... | 35 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_availab... | 35 | 1 |
'''simple docstring'''
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
... | 35 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_availab... | 35 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class a_ ( lowerCamelCase ):
def _... | 35 |
'''simple docstring'''
from math import factorial
def lowercase__ ( __UpperCamelCase = 20 )-> int:
UpperCamelCase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCamelCase ... | 35 | 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, ... | 35 |
'''simple docstring'''
from math import sqrt
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = 0
for i in range(1 , int(sqrt(__UpperCamelCase ) + 1 ) ):
if n % i == 0 and i != sqrt(__UpperCamelCase )... | 35 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class a_ :
lowercase = 42
lower... | 35 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 35 | 1 |
'''simple docstring'''
from collections import namedtuple
import requests
from lxml import html # type: ignore
SCREAMING_SNAKE_CASE__ = namedtuple('covid_data', 'cases deaths recovered')
def lowercase__ ( __UpperCamelCase = "https://www.worldometers.info/c... | 35 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase )-> str:
if not all(char in """01""" for char in bin_string ):
raise ValueError("""Non-binary value was passed to the function""" )
if not bin_string:
raise ValueError("""Empty str... | 35 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.a... | 35 |
'''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... | 35 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {
'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}
try:
if not ... | 35 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> str:
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance(__UpperCamelCase , __Up... | 35 | 1 |
'''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 imp... | 35 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def lowercase__ ( __UpperCamelCase , __UpperCamelCase=1 )-> Tuple:
if n_shave_prefix_segments >= 0:
return "... | 35 | 1 |
'''simple docstring'''
class a_ :
def __init__( self ) -> Tuple:
"""simple docstring"""
UpperCamelCase = """"""
UpperCamelCase = """"""
UpperCamelCase = []
def A__... | 35 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> dict[str, float]:
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("""One and only one argum... | 35 | 1 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
SCREAMING_SNAKE_CASE__ = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
... | 35 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keep... | 35 | 1 |
'''simple docstring'''
from __future__ import annotations
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE = 0 ) -> Tuple:
"""simple docstring"""
UpperCamelCase = key
def A__ ( self , _SCR... | 700 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser()
parse... | 35 | 0 |
'''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
... | 701 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE = 6 ) -> None:
"""simple docstring"""
UpperCamelCase = None
Upp... | 35 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor... | 702 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase=None , **__UpperCamelCase )-> int:
UpperCamelCase = [x.strip() for x in open(__UpperCame... | 35 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_av... | 703 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> tuple[float, list[float]]:
UpperCamelCase = list(range(len(__UpperCamelCase ) ) )
UpperCame... | 35 | 0 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
... | 704 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'SenseTime/deformable-detr... | 35 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowercase__ )
class a_ ( lowercase__ ):
lowerca... | 705 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowercase__ ( __UpperCamelCase )-> Any:
UpperCamelCase = [
"""encoder.version""",
... | 35 | 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... | 706 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 35 | 0 |
'''simple docstring'''
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets... | 707 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDM... | 35 | 0 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = {'''*''': op.mul, '''/''': op.truediv, '''+''': op.a... | 708 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
... | 35 | 0 |
'''simple docstring'''
def lowercase__ ( )-> Optional[Any]:
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(__lowerCAmelCase , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ =... | 709 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 8.31_44_62 # Unit - J mol-1 K-1
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError("""Invalid ... | 35 | 0 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class a_ ( logging.LoggerAdapter ):
@staticmethod
def A__ ( _SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCa... | 710 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set... | 35 | 0 |
'''simple docstring'''
from __future__ import annotations
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
UpperCamelCase = text, pattern
Uppe... | 711 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_availab... | 35 | 0 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE__ = list[list[int]]
# assigning initial values to the grid
SCREAMING_SNAKE_CASE__ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1... | 712 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_availab... | 35 | 0 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( _snake_case ):
lowercase = ['image_processor', 'tokenizer']
lowercase = 'CLIPImageProcessor'
lowercase = ('CLIPT... | 713 |
'''simple docstring'''
from math import factorial
def lowercase__ ( __UpperCamelCase = 20 )-> int:
UpperCamelCase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCamelCase ... | 35 | 0 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_... | 714 |
'''simple docstring'''
from math import sqrt
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = 0
for i in range(1 , int(sqrt(__UpperCamelCase ) + 1 ) ):
if n % i == 0 and i != sqrt(__UpperCamelCase )... | 35 | 0 |
'''simple docstring'''
import warnings
from .generation import TFGenerationMixin
class a_ ( __lowerCAmelCase ):
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed in Tr... | 715 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 35 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowercase__ ( __UpperCamelCase )-> Any:
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0X3400 and cp <= 0X4DBF) #
... | 716 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase )-> str:
if not all(char in """01""" for char in bin_string ):
raise ValueError("""Non-binary value was passed to the function""" )
if not bin_string:
raise ValueError("""Empty str... | 35 | 0 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> Any:
print("""\nThe shortest path matrix using Floyd Warshall algorithm\n""" )
for i in range(_lowerCamelCase ):
for j in range(_lowerCamelCase ):
... | 717 |
'''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... | 35 | 0 |
'''simple docstring'''
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowercase__ ( __UpperCamelCase )-> Any:
UpperCamelCase = [
'''decod... | 718 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> str:
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance(__UpperCamelCase , __Up... | 35 | 0 |
from __future__ import annotations
def lowercase__ ( __UpperCamelCase )-> None:
create_state_space_tree(_A , [] , 0 , [0 for i in range(len(_A ) )] )
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , ... | 719 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def lowercase__ ( __UpperCamelCase , __UpperCamelCase=1 )-> Tuple:
if n_shave_prefix_segments >= 0:
return "... | 35 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
... | 720 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> dict[str, float]:
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("""One and only one argum... | 35 | 0 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
... | 721 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keep... | 35 | 0 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from t... | 700 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser()
parse... | 35 | 0 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> Optional[Any]:
UpperCamelCase = sorted(zip(__SCREAMING_SNAKE_CASE... | 701 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE = 6 ) -> None:
"""simple docstring"""
UpperCamelCase = None
Upp... | 35 | 0 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from tran... | 702 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase=None , **__UpperCamelCase )-> int:
UpperCamelCase = [x.strip() for x in open(__UpperCame... | 35 | 0 |
from __future__ import annotations
from collections.abc import Callable
SCREAMING_SNAKE_CASE__ = list[list[float | int]]
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> List[Any]:
UpperCamelCase = len(snake_case_ )
... | 703 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> tuple[float, list[float]]:
UpperCamelCase = list(range(len(__UpperCamelCase ) ) )
UpperCame... | 35 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 704 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'SenseTime/deformable-detr... | 35 | 0 |
'''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformers... | 705 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowercase__ ( __UpperCamelCase )-> Any:
UpperCamelCase = [
"""encoder.version""",
... | 35 | 0 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tok... | 706 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 35 | 0 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils... | 707 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDM... | 35 | 0 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> int:
while a != 0:
UpperCamelCase = b % a, a
return b
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> int:
if ... | 708 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
... | 35 | 0 |
'''simple docstring'''
from __future__ import annotations
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE ) -> None:
"""simple docstring"""
UpperCamelCase = data
UpperCamelCase = ... | 709 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 8.31_44_62 # Unit - J mol-1 K-1
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError("""Invalid ... | 35 | 0 |
'''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... | 710 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set... | 35 | 0 |
'''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 a_ ( __UpperCAmelCase ):
def __in... | 711 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_availab... | 35 | 0 |
'''simple docstring'''
import random
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> str:
UpperCamelCase = [], [], []
for element in data:
if element < pivot:
less.append(_lowercase )
elif element > piv... | 712 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_availab... | 35 | 0 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_co... | 713 |
'''simple docstring'''
from math import factorial
def lowercase__ ( __UpperCamelCase = 20 )-> int:
UpperCamelCase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCamelCase ... | 35 | 0 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRA... | 714 |
'''simple docstring'''
from math import sqrt
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = 0
for i in range(1 , int(sqrt(__UpperCamelCase ) + 1 ) ):
if n % i == 0 and i != sqrt(__UpperCamelCase )... | 35 | 0 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logg... | 715 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 35 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''ut/deta''': '''https://huggingface.co/ut/d... | 716 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase )-> str:
if not all(char in """01""" for char in bin_string ):
raise ValueError("""Non-binary value was passed to the function""" )
if not bin_string:
raise ValueError("""Empty str... | 35 | 0 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
SCREAMING_SNAKE_CASE__ = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
SCREAMING_SNAKE_CASE__ = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: '... | 717 |
'''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... | 35 | 0 |
'''simple docstring'''
from typing import Any
import numpy as np
def lowercase__ ( __UpperCamelCase )-> Dict:
return np.array_equal(lowercase__ , matrix.conjugate().T )
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )->... | 718 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> str:
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance(__UpperCamelCase , __Up... | 35 | 0 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
SCREAMING_SNAKE_CASE__ = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membe... | 719 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def lowercase__ ( __UpperCamelCase , __UpperCamelCase=1 )-> Tuple:
if n_shave_prefix_segments >= 0:
return "... | 35 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.jso... | 720 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> dict[str, float]:
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("""One and only one argum... | 35 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClass... | 721 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keep... | 35 | 0 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class a_ ( lowerCamelCase ):
lowercase = (PNDMScheduler,)
lowercase = (('num_inference_steps', 50),)
def ... | 700 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser()
parse... | 35 | 0 |
'''simple docstring'''
from math import sqrt
def lowercase__ ( __UpperCamelCase = 1000000 )-> Union[str, Any]:
UpperCamelCase = 0
UpperCamelCase = 0
UpperCamelCase = 42
while num_cuboids <= ... | 701 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE = 6 ) -> None:
"""simple docstring"""
UpperCamelCase = None
Upp... | 35 | 0 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> str:
UpperCamelCase = ''''''
for i in table:
res += inp[i - 1]
return res
def lowercase__ ( __UpperCamelCase )-> int:
... | 702 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase=None , **__UpperCamelCase )-> int:
UpperCamelCase = [x.strip() for x in open(__UpperCame... | 35 | 0 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
SCREAMING_SNAKE_CASE__ = False
try:
... | 703 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> tuple[float, list[float]]:
UpperCamelCase = list(range(len(__UpperCamelCase ) ) )
UpperCame... | 35 | 0 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def lowercase__ ( __UpperCamelCase )-> Dict:
UpperCamelCase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_989 * r + 0.5_870 * g + 0.1_140 *... | 704 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'SenseTime/deformable-detr... | 35 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuratio... | 705 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowercase__ ( __UpperCamelCase )-> Any:
UpperCamelCase = [
"""encoder.version""",
... | 35 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
SCREAMING_SNAKE_CASE__ = '2020.9.26'
SCREAMING_SNAKE_CASE__ = 'xcodz-dot, cclaus, dhruvmanila'
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , ... | 706 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 35 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ = {
'configuration_efficientformer': [
... | 707 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDM... | 35 | 0 |
'''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_... | 708 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
... | 35 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
SCREAMING_SNAKE_CASE__ = False
class ... | 709 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 8.31_44_62 # Unit - J mol-1 K-1
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError("""Invalid ... | 35 | 0 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common ... | 710 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set... | 35 | 0 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin, SchedulerOutput
... | 711 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_availab... | 35 | 0 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPMo... | 712 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_availab... | 35 | 0 |
'''simple docstring'''
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class a_ ( __lowercase ):
def __init... | 713 |
'''simple docstring'''
from math import factorial
def lowercase__ ( __UpperCamelCase = 20 )-> int:
UpperCamelCase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCamelCase ... | 35 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = ... | 714 |
'''simple docstring'''
from math import sqrt
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = 0
for i in range(1 , int(sqrt(__UpperCamelCase ) + 1 ) ):
if n % i == 0 and i != sqrt(__UpperCamelCase )... | 35 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ ... | 715 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 35 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-smal... | 716 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase )-> str:
if not all(char in """01""" for char in bin_string ):
raise ValueError("""Non-binary value was passed to the function""" )
if not bin_string:
raise ValueError("""Empty str... | 35 | 0 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
SCREAMING_SNAKE_CASE__ = 'examples/'
SCREAMING_SNAKE_CASE__ = {
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),... | 717 |
'''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... | 35 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if... | 718 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> str:
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance(__UpperCamelCase , __Up... | 35 | 0 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
SCREAMING_SNAKE_CASE__ = 3
def lowercase__ ( __UpperCamelCase )-> int:
print("""Generating primitive root of p""" )
while Tru... | 719 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def lowercase__ ( __UpperCamelCase , __UpperCamelCase=1 )-> Tuple:
if n_shave_prefix_segments >= 0:
return "... | 35 | 0 |
import warnings
from ..trainer import Trainer
from ..utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class a_ ( __SCREAMING_SNAKE_CASE ):
def __init__( self , _SCREAMING_SNAKE_CASE=None , **_SCREAMING_SNAKE_CASE ... | 720 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> dict[str, float]:
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("""One and only one argum... | 35 | 0 |
'''simple docstring'''
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase = name
UpperCamelCase = va... | 721 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keep... | 35 | 0 |
'''simple docstring'''
import re
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = 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(__UpperCam... | 700 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser()
parse... | 35 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from ... | 701 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE = 6 ) -> None:
"""simple docstring"""
UpperCamelCase = None
Upp... | 35 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Pa... | 702 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase=None , **__UpperCamelCase )-> int:
UpperCamelCase = [x.strip() for x in open(__UpperCame... | 35 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 703 |
'''simple docstring'''
from __future__ import annotations
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> tuple[float, list[float]]:
UpperCamelCase = list(range(len(__UpperCamelCase ) ) )
UpperCame... | 35 | 0 |
'''simple docstring'''
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a_ ( nn.Module ):
def __init__( self , _SCREAMING_SNAKE_CASE = 16 , _SCREAMING_SNAKE_CASE = 88 , _SC... | 704 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'SenseTime/deformable-detr... | 35 | 0 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@r... | 705 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowercase__ ( __UpperCamelCase )-> Any:
UpperCamelCase = [
"""encoder.version""",
... | 35 | 0 |
'''simple docstring'''
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
SCREAMING_SNAKE_CASE__ = get_logger(__name__)
SCREAMING_SNAKE_CASE__ = R'\n Ar... | 706 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 35 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512... | 707 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDM... | 35 | 0 |
'''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstr... | 708 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
... | 35 | 0 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
SCREAMING_SNAKE_CASE__... | 709 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 8.31_44_62 # Unit - J mol-1 K-1
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError("""Invalid ... | 35 | 0 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = []
UpperCamelCase = []
UpperCamelCase = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'... | 710 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set... | 35 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transfo... | 711 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_availab... | 35 | 0 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> Any:
UpperCamelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total
def lowerc... | 712 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_availab... | 35 | 0 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manage... | 713 |
'''simple docstring'''
from math import factorial
def lowercase__ ( __UpperCamelCase = 20 )-> int:
UpperCamelCase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCamelCase ... | 35 | 0 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingS... | 714 |
'''simple docstring'''
from math import sqrt
def lowercase__ ( __UpperCamelCase )-> int:
UpperCamelCase = 0
for i in range(1 , int(sqrt(__UpperCamelCase ) + 1 ) ):
if n % i == 0 and i != sqrt(__UpperCamelCase )... | 35 | 0 |
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