code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
def snake_case_ ( __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
return base * power(__SCREAMING_SNAKE_CASE , (exponent - 1) ) if exponent else 1
if __name__... | 93 |
'''simple docstring'''
import argparse
import copy
def snake_case_ ( __SCREAMING_SNAKE_CASE : Optional[int] ):
"""simple docstring"""
lowercase_ : List[Any] = {}
with open(__SCREAMING_SNAKE_CASE ) as f:
... | 93 | 1 |
import os
import time
import numpy as np
import onnxruntime as ort
A_ : int = '1'
A_ : Any = '0'
A_ : Optional[int] = '1'
A_ : str = ort.SessionOptions()
A_ : Any = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print('Create inference session...')
A_ : Tuple = ['... | 141 |
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ort
A_ : Union[str, An... | 141 | 1 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...test_config... | 343 | from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE_ ( __lowerCAmelCase ):
pass
class SCREAMING_SNAKE_CASE_ :
def __init__( self : List[Any] , lowerCamelCase_ : Any ):
"""simple docstring"""
UpperCamelCase = d... | 343 | 1 |
def UpperCamelCase ( ):
"""simple docstring"""
for n in range(1, 1000000 ):
yield n * (n + 1) // 2
def UpperCamelCase ( _A ):
"""simple docstring"""
__magic_name__ : Tuple ... | 351 |
import os
from pathlib import Path
def UpperCamelCase ( ):
"""simple docstring"""
from torch.utils.cpp_extension import load
__magic_name__ : Dict = Path(_A ).resolve().parent.parent.parent / """kernels""" / """deformable_detr"""
__magic_nam... | 138 | 0 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
rais... | 260 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert impor... | 296 | 0 |
from __future__ import annotations
def A_ ( _lowerCAmelCase , _lowerCAmelCase ) -> list[str]:
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_bytes:
raise ValueError("partitions can not > number_of_bytes!" )
... | 140 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class A__ ( __snake_case ):
def _... | 140 | 1 |
'''simple docstring'''
def UpperCamelCase__ ( lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = len(lowerCAmelCase )
for i in range(length - 1 ):
_lowerCAmelCase = i
for k in rang... | 70 |
"""simple docstring"""
from math import pow, sqrt
def lowerCamelCase__ ( *_lowerCamelCase : float ) -> bool:
lowerCamelCase_ = len(_lowerCamelCase ) > 0 and all(value > 0.0 for value in values )
return result
def ... | 183 | 0 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we had to include /h... | 365 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common impor... | 139 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require_t... | 141 |
'''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class lowerCAmelCase ( A ):
def __init__( self : Optional[Any] , *__lowercase : str , **__lowercase : Union[str, Any] ):
"""simple docstrin... | 141 | 1 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def lowerCAmelCase_ ( __A, __A, __A, __A=1_024 ) -> Optional[int]:
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCas... | 143 | from __future__ import annotations
def lowerCAmelCase_ ( __A, __A, __A, ) -> tuple:
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("You cannot supply more or less than 2 values" ... | 143 | 1 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class A__ ( nn.Module):
A_ : int
A_ : int
A_ : float = 0... | 86 |
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
__A : Tuple = {
'''User-Agent''': '''Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'''
''' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582'''
}
de... | 138 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class lowercase ( a_ ):
_a ... | 358 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterMixin
from ...t... | 343 | 0 |
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL i... | 140 | 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 (
is_accelerate_available,
is_... | 140 | 1 |
'''simple docstring'''
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
_a : List[Any] = logging.get_logger(__name__)
class _UpperCAmelCase ( lowerCAmelCase_ ... | 369 |
'''simple docstring'''
import sys
def _lowerCAmelCase ( lowercase ) -> List[str]:
__lowerCAmelCase = len(lowercase )
__lowerCAmelCase = [[0 for x in range(lowercase )] for x in range(lowercase )]
__lowerCAmelCase = [[0 for x in range... | 46 | 0 |
'''simple docstring'''
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A =logging.get_logger(__name__)
A ={
'kakaobrain/align-base': 'https://huggingface.co/kakaob... | 34 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
A_ = logging.get_logger(__name__)
class _snake_case ( _a ):
def __init__( self : Optional[int] ,*SCREAMING_SNAKE_CASE__ : ... | 139 | 0 |
'''simple docstring'''
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def __lowerCamelCase ( A__ , A__ , A__ ) -> Optional[int]:
"""simple docstring"""
UpperCam... | 249 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from tra... | 249 | 1 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __snake_case ( yaml.SafeLoader ):
def __a ( self , __UpperCamelCase ) -> str:
'''simple docstring'''
snake_case__ ... | 143 | import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.... | 143 | 1 |
from pathlib import Path
import fire
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowercase__ = Path(SCREAMING_SNAKE_CASE_ )
lowercase__ = Path(SCREAMING_SNAKE_CASE_ )
dest_dir.mkdir(exist_ok=SCREAMING_SNAK... | 224 |
import argparse
import json
import subprocess
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowercase__ = []
lowercase__ = (
f'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'''
" https://api.github... | 224 | 1 |
"""simple docstring"""
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
_lowercase = (
'''This metric will be removed from the library so... | 74 | import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_SCREAMING... | 343 | 0 |
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():... | 371 | import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'''vocab_file''': '''vocab.json''',
'''merges_file... | 63 | 0 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def lowercase ( A_ )-> Optional[int]:
'''simple docstring'''
a : str = [
... | 40 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import P... | 46 | 0 |
from math import pi, sqrt, tan
def a_ ( lowerCAmelCase_ : float ):
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def a_ ( lowerCAmelCase_ : float, lowerCAmelCase_ : float, lo... | 368 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils imp... | 207 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
a_ = {'processing_wav2vec2_with_lm': ['Wav2Vec2ProcessorWithLM']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
a_ = _... | 249 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_deter... | 364 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ = 2000000 ):
UpperCAmelCase_ = [0 for i in range(n + 1 )]
UpperCAmelCase_ = 1
UpperCAmelCase_ = 1
for i in range(2 , int(n**0.5 ) + 1 ):
... | 241 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=lowercase_ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = ["""flax"""]
def __init__( self : List... | 224 |
"""simple docstring"""
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
... | 224 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
A = "2020.9.26"
A = "xcodz-dot, cclaus, dhruvmanila"
def __A ( a_ :float , a_ :float , a_ :float , a_ :float , a_ :float) -> tuple[float, float]:
... | 357 |
"""simple docstring"""
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mo... | 188 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DUMMY_... | 314 |
'''simple docstring'''
import math
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def UpperCamelCase__ ( self : List[str] , __a : list[list[float]] , __a : list[int] ):
_a = 0.0
_a = 0.0
fo... | 63 | 0 |
'''simple docstring'''
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
def update_area_of_max_square(__lowerCAmelCase , __lowerCAmelCase ) -> int:
# BASE CASE
if row >= rows or col >= cols:
return 0
_UpperCAmelCase : Optional[Any] ... | 356 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
... | 322 | 0 |
"""simple docstring"""
from functools import lru_cache
@lru_cache
def _snake_case ( lowercase__ ):
if num < 0:
raise ValueError('Number should not be negative.' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main... | 96 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requ... | 207 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransfo... | 240 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, ... | 240 | 1 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__UpperCAmelCase = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n author={Yonghui Wu and Mi... | 299 |
"""simple docstring"""
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 241 | 0 |
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
__a = _symbol_database.Def... | 366 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__a = {
'configuration_bloom': ['BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BloomConfig', 'BloomOnnxConfig'],
}
try:
if not is_tokenizers_available():
... | 235 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase_ : List[Any] = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.c... | 91 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase = {
'''configuration_deberta''': ['''DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DebertaConfig''... | 188 | 0 |
import argparse
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_seed
from accelerate import Accelerator, DistributedTyp... | 169 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from .... | 169 | 1 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__lowerCAmelCase : str = ''
__lowerCAmelCase : Tuple = ''
__lowerCAmelCase : Tuple = ''
__lowerCAmelCase : Optional[int] = 1 # (0 is vertical, 1 ... | 88 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMix... | 322 | 0 |
'''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 HfDoctestModul... | 13 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
fr... | 13 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 240 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __lowercase ( ):
a__ = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
a__ = parser.add_subparsers(help='diffusers-cli command helpers' ... | 240 | 1 |
from __future__ import annotations
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , ) -> tuple[str, float]:
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('You cannot supply more or less than 2 values' )
elif stress < 0:
... | 292 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...t... | 292 | 1 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def a__ ( _UpperCamelCase : Any ):
__lowerCamelCase = int(__a )
__lowerCamelCas... | 330 |
a__ = '''0.18.2'''
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_librosa_available,
is_n... | 235 | 0 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : list[list[int]] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : set ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ = le... | 360 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 61 | 0 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
_lowerCAmelCase : int = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase ):
def __init__( self :Tuple , *lowerCamelCase :Dict , ... | 169 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is_vision_ava... | 169 | 1 |
def UpperCamelCase_( snake_case__: int = 50 ) -> List[Any]:
UpperCAmelCase__ = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
ways_number[row... | 356 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',
... | 335 | 0 |
# 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, HfDocTestParser
# allow having multiple repository ... | 13 |
def A_ ( _UpperCAmelCase , _UpperCAmelCase = False ):
if not isinstance(_UpperCAmelCase , _UpperCAmelCase ):
SCREAMING_SNAKE_CASE_: str = f"Expected string as input, found {type(_UpperCAmelCase )}"
raise ValueError(_UpperCAmelCase )
if not isi... | 13 | 1 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
A : Optional[Any] = [int(0.5 * n * (n + 1)) for n in range(1, 1_01)]
def a__ ( ):
SCREAMING_SNAKE_CASE_ = os.path.dirname(os.path.realpath(lowercase_ ) )
SC... | 362 | import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def a__ ( __UpperCamelCase ):
return x + 2
class lowerCamelCase (unittest.TestCase ):
"""simple docstring"""
def __A ( self : ... | 305 | 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
_snake_case : List[str] = get_logger(__name__)
_snake_case : List[Any] = r'\n Args:\n inp... | 292 |
"""simple docstring"""
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to... | 292 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase__ = {
"""configuration_xlm""": ["""XLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMConfig""", """XLMOnnxConfig"""],
"""tokenization_xlm""": ["""XLMToken... | 363 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
UpperCAmelCase__ = logging.get_logger(__name__)
class a ( lowerCAmelCase_ ):
_snake_case : List[str] ... | 30 | 0 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
_a : int = [
"encoder.vers... | 294 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class A_ :
'''simple docstring'''
pass
| 61 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimen... | 90 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase : str = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 42 |
"""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 ImageProcessingSavingT... | 335 | 0 |
'''simple docstring'''
class lowercase__ :
def __init__( self : List[str] ,lowerCamelCase__ : List[Any] ,lowerCamelCase__ : Optional[int] ,lowerCamelCase__ : Any ):
'''simple docstring'''
_UpperCamelCase : Dict = None
_UpperCamelCase : ... | 236 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
snake_case_ : List[Any] = logging.get_logger(__name__)
snake_case_ ... | 236 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : int = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwritt... | 27 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 305 | 0 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
UpperCamelCase__ = logging.get_l... | 356 |
'''simple docstring'''
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'''post_extrac... | 299 | 0 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import c... | 62 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelO... | 30 | 0 |
_snake_case = tuple[float, float, float]
_snake_case = tuple[float, float, float]
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[Any] = end_pointa[0] - end_pointa[0]
_lowerCAmelCase : str ... | 350 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( a):
def __init__( self, *__a, **__a):
'''simple docstring'''
warnings.... | 300 | 0 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowerCamelCase_ ( UpperCamelCase__ : dict ... | 90 |
from math import sqrt
def lowerCamelCase_ ( UpperCamelCase__ : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 90 | 1 |
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
@require_tokenizers
@requ... | 358 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Optional[int] = logging.get_logger(__name__)
UpperCamelCase__ : Dict = {
"""facebook/vit-mae-base""": """https://huggingface.co/facebook/vit-mae-base/resolve/main/config.js... | 330 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __lowerCAmelCase ( lowerCAmelCase):
@staticmethod
@abstractmethod
def SCREAMING_SNAKE_CASE ( _lowerCAmelCase: ArgumentParser ):
raise NotImplementedError()
... | 236 |
import torch
def UpperCAmelCase__ ( ):
if torch.cuda.is_available():
lowercase :Optional[int] = torch.cuda.device_count()
else:
lowercase :Dict = 0
print(F"Successfully ran on {num_gpus} GPUs" )
if __name__ == "__main__":
main()
| 236 | 1 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Tra... | 300 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impo... | 300 | 1 |
'''simple docstring'''
UpperCamelCase_ = """\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"""
UpperCamelCa... | 309 |
def A__ ( __lowerCamelCase ):
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
'''%''': 2,
'''+''': 1,
'''-''': 1,
} # Priority of each operator
SCREAMING_SNAKE_CASE_ ... | 299 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase_ ={
"""configuration_mgp_str""": ["""MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MgpstrConfig"""],
"""processing_mgp_str""": ["""MgpstrProcessor"""]... | 362 |
"""simple docstring"""
def a_ ( _lowercase , _lowercase ):
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows list cannot be empty''' )
_Upp... | 128 | 0 |
from __future__ import annotations
def __snake_case ( _lowerCAmelCase : list[float] ) -> bool:
if len(_lowerCAmelCase ) < 2:
raise ValueError("Monogons and Digons are not polygons in the Euclidean space" )
if any(i <= 0 for i in nums ):
raise ValueError("All values... | 300 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import Pa... | 300 | 1 |
'''simple docstring'''
from __future__ import annotations
class _A :
def __init__( self : str , __magic_name__ : Optional[Any]=None ) -> Tuple:
"""simple docstring"""
__snake_case : Optional[Any] = data
__snake_cas... | 13 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require... | 13 | 1 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
'snap-research/efficientformer-l1-300': (
'https://huggingface.co/snap-research/efficientforme... | 110 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_para... | 330 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase : int = logging.get_logger(__name__)
lowerCAmelCase : Dict = {
"""speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrai... | 25 |
'''simple docstring'''
from math import isqrt
def lowercase (_A ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(_A ) + 1 ) )
def lowercase (_A = 1_0**6 ):
... | 25 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
_lowerCAmelCase : List[Any] = {'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfi... | 300 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
class __magic_name__ ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self :Unio... | 300 | 1 |
import numpy as np
def UpperCamelCase ( __lowerCamelCase : np.array ):
return 1 / (1 + np.exp(-vector ))
def UpperCamelCase ( __lowerCamelCase : np.array ):
return vector * sigmoid(1.702 * vector )
if __name__ == "__main__":
import doctest
d... | 350 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = """▁"""
__lowerCam... | 10 | 0 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmentation,
... | 9 |
class _lowercase :
'''simple docstring'''
def __init__( self , snake_case__ ):
'''simple docstring'''
UpperCamelCase_ = arr.split("," )
def _lowerCamelCase ( self ):
'''simple docstring'''
UpperC... | 128 | 0 |
def __UpperCAmelCase ( __a : int ,__a : int ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(0 ) == 0 )
def __UpperCAmelCase ( ) -> None:
"""simple docstring"""
assert and_gate(0 ,0 ... | 15 |
from math import ceil
def __UpperCAmelCase ( __a : int = 1_001 ) -> int:
"""simple docstring"""
_a : Dict = 1
for i in range(1 ,int(ceil(n / 2.0 ) ) ):
_a : int = 2 * i + 1
_a : ... | 15 | 1 |
from __future__ import annotations
class __lowercase :
"""simple docstring"""
def __init__( self : Dict , lowerCAmelCase__ : List[Any]=None):
SCREAMING_SNAKE_CASE_: str = data
SCREAMING_SNAKE_CASE_: Optional[int] = None
def __repr__(... | 13 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase : Any = logging.get_logger(__name__)
lowerCAmelCase : Tuple = ... | 13 | 1 |
'''simple docstring'''
from math import ceil
def lowerCAmelCase__ ( lowerCamelCase : Tuple ,lowerCamelCase : int ):
_A : str = list(range(0 ,lowerCamelCase ) )
_A : Union[str, Any] = [item for sublist in list(device_map.... | 227 |
'''simple docstring'''
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from ... | 227 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ : str... | 25 |
"""simple docstring"""
UpperCAmelCase__ : Any = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transform... | 25 | 1 |
def __lowercase ( a__ ) -> list:
if len(a__ ) <= 1:
return [tuple(a__ )]
__SCREAMING_SNAKE_CASE = []
def generate(a__ , a__ ):
if k == 1:
res.append(tuple(arr[:] ) )
... | 118 |
lowerCAmelCase__ : Optional[int] =9.80_665
def __lowercase ( a__ , a__ , a__ = g ) -> float:
if fluid_density <= 0:
raise ValueError('Impossible fluid density' )
if volume < 0:
raise ValueError('Impossi... | 118 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrai... | 323 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowerCAmelCase_ ( ) -> Optional[int]:
"""simple docstring"""
lowerCamelCase__ , lowerCamelCase__: int =9, 14 # noqa: F841
lowerCamelCase__: Lis... | 10 | 0 |
'''simple docstring'''
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging impo... | 355 |
'''simple docstring'''
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def lowerCAmelCase__ ( low... | 227 | 0 |
def UpperCAmelCase ( a_ , a_ ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(0 ) == 0 )
def UpperCAmelCase ( ) -> None:
"""simple docstring"""
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
... | 15 |
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 15 | 1 |
from manim import *
class UpperCAmelCase_ ( _a):
'''simple docstring'''
def _lowercase ( self ):
"""simple docstring"""
UpperCamelCase : Optional[int] = Rectangle(height=0.5 , width=0.5 )
... | 315 |
def a ( SCREAMING_SNAKE_CASE_ : str = "The quick brown fox jumps over the lazy dog" , ):
"""simple docstring"""
UpperCamelCase : Any = set()
# Replace all the whitespace in our sentence
UpperCamelCase : Unio... | 315 | 1 |
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_available():
from .tokenization_camembert imp... | 227 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase: Union[str, Any] = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BridgeTowerConfig",
"BridgeT... | 227 | 1 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def SCREAMING_SNAKE_CASE__( _UpperCamelCase : int = 3 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
... | 31 |
'''simple docstring'''
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from t... | 31 | 1 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def a__ ( __UpperCamelCase , __UpperCamelCase ):
SCREAMING_SNAKE_CASE_ = k_size // 2
SCREAMING_SNAKE_CASE_ , ... | 118 | from __future__ import annotations
class lowerCamelCase :
"""simple docstring"""
def __init__( self : Union[str, Any] , __magic_name__ : str , __magic_name__ : str ) -> Dict:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = ... | 118 | 1 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 371 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
lowerCAmelCase__ = namedtuple(
'''_TestCom... | 244 | 0 |
from __future__ import annotations
lowerCAmelCase_ = list[list[int]]
# assigning initial values to the grid
lowerCAmelCase_ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0, 5... | 8 |
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class _lowercase ( lowerCAmelCase ):
"""simple docstring"""
def __init__(self , lowerCamelCase_ , lowerCamelCase_ ):
""... | 227 | 0 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
__s... | 359 |
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from transformers.file_ut... | 122 | 0 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: ... | 315 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/config.json''',
'''xlnet-large-cased''': '''https:/... | 315 | 1 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : List[Any] = 2**power
_UpperCamelCase : Tuple = str(UpperCAmelCase_ )
_UpperCamelCase : Union[str, Any] = list(UpperCAmelCase_ )
_UpperCamelCase : Tu... | 236 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
snak... | 236 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Any = {
"""studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/res... | 31 | '''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
__SCREAMING_SNAKE_CASE : ... | 31 | 1 |
def lowerCAmelCase_ ( __UpperCAmelCase: str ) -> str:
return "".join(chr(ord(__UpperCAmelCase ) - 32 ) if '''a''' <= char <= '''z''' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 247 |
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__ ( unittest.TestCase ):
... | 247 | 1 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class UpperCame... | 172 |
lowerCamelCase_ = frozenset(
[
'''prompt''',
'''height''',
'''width''',
'''guidance_scale''',
'''negative_prompt''',
'''prompt_embeds''',
'''negative_prompt_embeds''',
'''cross_attention_kwargs''',
]
)
lowerCamelCase_ = frozen... | 244 | 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... | 354 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class lowerCAmelCase__ ( logging.LoggerAdapter ):
@staticmethod
def _snake_case ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
... | 264 | 0 |
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
_lowerCamelCase : List[Any] = logging.get_logger(__name__)... | 336 |
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase__ ( a__ : float , a__ : float , a__ : int ) -> float:
UpperCamelCase_ = x
UpperCamelCase_ = y
for step in range(a__ ): # noqa: B007
U... | 122 | 0 |
from __future__ import annotations
import bisect
def _a ( a :list[int] , a :int , a :int = 0 , a :int = -1 ) -> int:
if hi < 0:
a = len(a )
while lo < hi:
a = lo + (hi - lo) // 2
if sorted_collection[mid] < item... | 26 |
import math
def _a ( a :int = 100 ) -> int:
a = sum(i * i for i in range(1 , n + 1 ) )
a = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return square_of_sum - sum_of_squares
if __name__ == "__main__":
print(f... | 26 | 1 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common ... | 236 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
_UpperCAmelCase : Tuple = {
"susnato/ernie-m-base_pytorch": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json",
"susnato/ernie-m-large_pytorch": "https://huggingfa... | 236 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartToken... | 208 |
import math
def _SCREAMING_SNAKE_CASE ( lowercase : int ):
'''simple docstring'''
lowerCamelCase_ = 0
lowerCamelCase_ = 0
while num > 0:
lowerCamelCase_ = num % 8
lowerCamelCase_ = octal... | 208 | 1 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
A__ = [[0 for _ in range(lowercase_ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
A__ = 1
for n in range(m + 1 ):
for k in range(1 , lowercase_ ):
memo[n][k] ... | 247 |
"""simple docstring"""
import os
from pathlib import Path
def _SCREAMING_SNAKE_CASE ( ) -> Tuple:
from torch.utils.cpp_extension import load
A__ = Path(lowercase_ ).resolve().parent.parent.parent / "kernels" / "deformable_detr"
A__ = [
root / filename
... | 247 | 1 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
__lowercase = {
'''linear''': PIL.Image.Resampling.BILINEAR,
'''bilinear''': PIL.Image.Resampling.BILINEAR,... | 105 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 105 | 1 |
'''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_increases
def lowerCa... | 331 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : str = {
'''configuration_x_clip''': [
'''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XCLIPConfig''',
'''XCLIPTextCon... | 264 | 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_available():
from tran... | 267 |
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, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor, loa... | 267 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils impo... | 26 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class lowercase ( UpperCamelCase__ ):
_a = (DPMSol... | 26 | 1 |
'''simple docstring'''
from __future__ import annotations
A__ : Optional[int] = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],... | 0 |
'''simple docstring'''
from __future__ import annotations
A__ : str = '''Muhammad Umer Farooq'''
A__ : int = '''MIT'''
A__ : Optional[int] = '''1.0.0'''
A__ : List[Any] = '''Muhammad Umer Farooq'''
A__ : Optional[Any] = '''contact@muhammadumerfa... | 0 | 1 |
'''simple docstring'''
import logging
from transformers import PretrainedConfig
_UpperCamelCase = logging.getLogger(__name__)
_UpperCamelCase = {
'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summ... | 208 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentence... | 208 | 1 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
_snake_case = False
class a__ ( unittest.TestCase ):
def _lowerCamelCase ( self ... | 360 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = '▁'
_snake_case = {'vocab_file': 'spiece.model'}
_snake_... | 199 | 0 |
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